The "self-similarity logic" applied to the development of the vascular system

A Self-Similarity Logic May Shape the Organization of the Nervous System

From the morphological point of view, the nervous system exhibits a fractal, self-similar geometry at various levels of observations, from single cells up to cell networks. From the functional point of view, it is characterized by a hierarchical organization in which self-similar structures (networks) of different miniaturizations are nested within each other. In particular, neuronal networks, interconnected to form neuronal systems, are formed by neurons, which operate thanks to their molecular networks, mainly having proteins as components that via protein-protein interactions can be assembled in multimeric complexes working as micro-devices. On this basis, the term "self-similarity logic" was introduced to describe a nested organization where, at the various levels, almost the same rules (logic) to perform operations are used. Self-similarity and self-similarity logic both appear to be intimately linked to the biophysical evidence for the nervous system being a pattern-forming system that can flexibly switch from one coherent state to another. Thus, they can represent the key concepts to describe its complexity and its concerted, holistic behavior.

Spatial Statistics-Based Image Analysis Methods for the Study of Vascular Morphogenesis

Several studies are available addressing the mechanisms of vascular morphogenesis in order to unravel how cooperative cell behavior can follow from the underlying, genetically regulated behavior of endothelial cells and from cell-to-cell and cell-to-extracellular matrix interactions. From the morphological standpoint several aspects of the process are of interest. They include the way the pattern of vessels fills the available tissue space and how the network grows during the angiogenic process, namely how a main trunk divides into smaller branches, and how branching occurs at different distances from the root point of a vascular tree. A third morphological aspect of interest concerns the spatial relationship between vessels and tissue cells able to secrete factors modulating endothelial cells self-organization, thus influencing vascular rearrangement.In the present chapter image analysis methods allowing for a quantitative characterization of these morphological aspects will be detailed and discussed. They are almost based on concepts derived from the theoretical framework represented by spatial statistics.

Immunotherapeutic strategies in pancreatic ductal adenocarcinoma (PDAC): current perspectives and future prospects

Pancreatic ductal adenocarcinoma (PDAC) is among the deadliest human malignancies with a dismal prognosis. During PDAC progression, the immune response is affected as cancer cells evade detection and elimination. Recently, there have been advances in the treatment of PDAC using immunotherapy, although a lot more work is yet to be done. In this review, we discuss these advances, challenges and potentials. We focus on existing and potential immune targets for PDAC, drugs used to target them, and some clinical trials conducted so far with them. Finally, novel targets in the tumour microenvironment such as stromal cells and other potential future areas to explore including bacterial therapy and the use of neoantigens in immunotherapy are highlighted.

Investigating in vitro angiogenesis by computer-assisted image analysis and computational simulation

In vitro assays that stimulate the formation of capillary-like structures by EC have become increasingly popular, because they allow the study of the EC's intrinsic ability to self-organize to form vascular-like patterns. Here we describe a widely applied protocol involving the use of basement membrane matrix (Matrigel) as a suitable environment to induce an angiogenic phenotype in cultured EC. EC differentiation on basement membrane matrix is a highly specific process, which recapitulates many steps in blood vessel formation and for this reason it is presently considered as a reliable in vitro tool to identify factors with potential antiangiogenic or pro-angiogenic properties. The morphological features of the obtained cell patterns can also be accurately quantified by computer-assisted image analysis and the main steps of such a procedure will be here outlined and discussed. The dynamics of in vitro EC self-organization is a complex biological process, involving a network of interactions between a high number of cells. For this reason, the combined use of in vitro experiments and computational modeling can represent a key approach to unravel how mechanical and chemical signaling by EC coordinates their organization into capillary-like tubes. Thus, a particularly helpful approach to modeling is also briefly described together with examples of its application.

Fractal dimension of chromatin: potential molecular diagnostic applications for cancer prognosis

Fractal characteristics of chromatin, revealed by light or electron microscopy, have been reported during the last 20 years. Fractal features can easily be estimated in digitalized microscopic images and are helpful for diagnosis and prognosis of neoplasias. During carcinogenesis and tumor progression, an increase of the fractal dimension (FD) of stained nuclei has been shown in intraepithelial lesions of the uterine cervix and the anus, oral squamous cell carcinomas or adenocarcinomas of the pancreas. Furthermore, an increased FD of chromatin is an unfavorable prognostic factor in squamous cell carcinomas of the oral cavity and the larynx, melanomas and multiple myelomas. High goodness-of-fit of the regression line of the FD is a favorable prognostic factor in acute leukemias and multiple myelomas. The nucleus has fractal and power-law organization in several different levels, which might in part be interrelated. Some possible relations between modifications of the chromatin organization during carcinogenesis and tumor progression and an increase of the FD of stained chromatin are suggested. Furthermore, increased complexity of the chromatin structure, loss of heterochromatin and a less-perfect self-organization of the nucleus in aggressive neoplasias are discussed.

Expansion of the fetoplacental vasculature in late gestation is strain dependent in mice

How the fetoplacental arterial tree grows and expands during late gestational development is largely unknown. In this study, we quantified changes in arterial branching in the fetal exchange region of the mouse placenta during late gestation, when capillarization increases rapidly. We studied two commonly used mouse strains, CD1 and C57Bl/6 (B6), at embryonic days (E)13.5, 15.5, and 17.5. B6 mice differ from CD1 mice by exhibiting a blunted fetal weight gain in late gestation. We found that B6 capillarization and interhemal membrane thinning were reduced and placental hypoxia-inducible factor-1α and VEGF-A expression were higher than CD1 near term. Automated vascular segmentation of microcomputed tomography data sets revealed that the number of arterial vessels ≥50 μm remained constant during late gestation in both strains, despite large increases in downstream capillary volume quantified by stereology (+65% in B6 mice and +200% in CD1 mice). Arterial diameters expanded in both strains from E13.5 to E15.5; however, diameters continued to expand to E17.5 in B6 mice only. The diameter scaling coefficient at branch sites was near optimal (-3.0) and remained constant in CD1 mice, whereas it decreased, becoming abnormal, in B6 mice at term (-3.5 ± 0.2). Based on arterial tree geometry, resistance remained constant throughout late gestation (∼0.45 mmHg·s·μl(-1)) in CD1 mice, whereas it decreased by 50% in late gestation in B6 mice. Quantification of the fetoplacental vasculature revealed significant strain-dependent differences in arterial and capillary expansion in late gestation. In both strains, enlargement of the fetoplacental arterial tree occurred primarily by increased arterial diameters with no change in segment numbers in late gestation.

Cell-oriented modeling of angiogenesis

Due to its significant involvement in various physiological and pathological conditions, angiogenesis (the development of new blood vessels from an existing vasculature) represents an important area of the actual biological research and a field in which mathematical modeling proved particularly useful in supporting the experimental work. In this paper, we focus on a specific modeling strategy, known as "cell-centered" approach. This type of mathematical models work at a "mesoscopic scale," assuming the cell as the natural level of abstraction for computational modeling of development. They treat cells phenomenologically, considering their essential behaviors to study how tissue structure and organization emerge from the collective dynamics of multiple cells. The main contributions of the cell-oriented approach to the study of the angiogenic process will be described. From one side, they have generated "basic science understanding" about the process of capillary assembly during development, growth, and pathology. On the other side, models were also developed supporting "applied biomedical research" for the purpose of identifying new therapeutic targets and clinically relevant approaches for either inhibiting or stimulating angiogenesis.