Modeling the extracellular matrix in cell migration and morphogenesis:a guide for the curious biologist

The extracellular matrix (ECM) is a highly complex structure through which biochemical and mechanical signals are transmitted. In processes of cell migration, the ECM also acts as a scaffold, providing structural support to cells as well as points of potential attachment. Although the ECM is a well-studied structure, its role in many biological processes remains difficult to investigate comprehensively due to its complexity and structural variation within an organism. In tandem with experiments, mathematical models are helpful in refining and testing hypotheses, generating predictions, and exploring conditions outside the scope of experiments. Such models can be combined and calibrated with in vivo and in vitro data to identify critical cell-ECM interactions that drive developmental and homeostatic processes, or the progression of diseases. In this review, we focus on mathematical and computational models of the ECM in processes such as cell migration including cancer metastasis, and in tissue structure and morphogenesis. By highlighting the predictive power of these models, we aim to help bridge the gap between experimental and computational approaches to studying the ECM and to provide guidance on selecting an appropriate model framework to complement corresponding experimental studies

Colorimetric characterization of ochres in a Palaeolithic flint pebble from Maschio dell’Artemisio, Latium, Italy

The flint pebble from Maschio dell’Artemisio, a peak of the Artemisio mountain range (South-East of Rome), represents one of the first complex artefacts from the Upper Palaeolithic of the Alban Hills possibly displaying a symbolic/artistic value (Altamura & Mussi, 2014). It has been used as a hammer stone and retoucher, to create or modify lithic implements. It shows a diffuse and intense ochraceous colour on almost half of its surface. In the present work we discuss the results of an innovative colorimetric approach to define the use of pigments in the Palaeolithic community of the area and eventually compare the raw materials with local supplies. Second-derivative diffuse reflectance spectroscopy (DRS) is a data treatment on colorimetric data used from the ‘80s in the characterization of soil (Scheinost et al., 1998). More recently, it has been applied on iron oxide and hydroxide minerals, to investigate their colour and crystal properties (Torrent & Barrón, 2003). Here it was used directly on an archaeological artefact, to determine the presence of yellow and red ochres, but also to quantify the amount of each pigment present in mixture on the surface. Data were acquired using either a colorimeter and fibre optic reflectance spectroscopy (FORS) and then compared to test the efficiency of both techniques. Altamura F., Mussi M., Arte mobiliare paleolitica dalla Catena del Tuscolano-Artemisio, Lazio e Sabina 10 (2014), Atti del Convegno Decimo Incontro di Studi sul Lazio e la Sabina, Roma, 4-6 Giugno 2013, pp. 119-125 Scheinost A. C., Chavernas A., Barrón V., Torrent J., Use and limitations of second-derivative diffuse reflectance spectroscopy in the visible to near-infrared range to identify and quantify Fe oxide minerals in soils, Clays and Clay Minerals, 46(1998), 528-536 Torrent J., Barrón V., The visible diffuse reflectance spectrum in relation to the color and crystal properties of hematite,Clays and Clay Minerals, 51(2003), 309-31

Prognosis of elderly gastric cancer patients after surgery: a nomogram to predict survival.

This study aimed to identify clinicopathological factors associated with the outcome of elderly patients with gastric cancer (GC), and to construct a nomogram for individual risk prediction. Tumor characteristics of 143 patients aged ≥ 80 years underwent surgery for GC were collected and analyzed by uni- and multivariate analyses. A prognostic nomogram was constructed using the factors which resulted to be significantly associated with overall survival. Discrimination of nomogram was tested by Kaplan-Meier (KM) curves and boxplots. With a median follow up of 18.37 months, overall 1-year survival rate was 51% and it was 60 and 40% for older and younger than 83 years, respectively (P = 0.003). Univariate analysis indicated that age (P = 0.008), pre-operatory performance status (P < 0.001), depth of invasion (P = 0.007), lymph nodes involvement (P < 0.001), and residual tumor (P < 0.001) were significant prognostic factors. Based on these variables, a nomogram to predict 3, 6, 12, and 24 months survival probability after GC surgery was developed. KM and boxplots according to the range of nomogram total points highlighted the appropriateness of distinguish the patients' survival in all the subgroups. Moreover, this nomogram exhibited superior prognostic discrimination between intermediate stages (II-III) than AJCC-TNM classification. This study showed that after good surgical selection, the prognosis of elderly GC patients may be influenced by several clinicopathological factors. Therefore, a predictive nomogram to distinguish more accurately fit patients may allow physicians to individualize treatments and to detect those patients who may benefit from an intensive multidisciplinary approach