Syndecan-1 Depletion Has a Differential Impact on Hyaluronic Acid Metabolism and Tumor Cell Behavior in Luminal and Triple-Negative Breast Cancer Cells

Glycosaminoglycans (GAGs) and proteoglycans (PGs) are major components of the glycocalyx. The secreted GAG and CD44 ligand hyaluronic acid (HA), and the cell surface PG syndecan-1 (Sdc-1) modulate the expression and activity of cytokines, chemokines, growth factors, and adhesion molecules, acting as critical regulators of tumor cell behavior. Here, we studied the effect of Sdc-1 siRNA depletion and HA treatment on hallmark processes of cancer in breast cancer cell lines of different levels of aggressiveness. We analyzed HA synthesis, and parameters relevant to tumor progression, including the stem cell phenotype, Wnt signaling constituents, cell cycle progression and apoptosis, and angiogenic markers in luminal MCF-7 and triple-negative MDA-MB-231 cells. Sdc-1 knockdown enhanced HAS-2 synthesis and HA binding in MCF-7, but not in MDA-MB-231 cells. Sdc-1-depleted MDA-MB-231 cells showed a reduced CD24-/CD44+ population. Furthermore, Sdc-1 depletion was associated with survival signals in both cell lines, affecting cell cycle progression and apoptosis evasion. These changes were linked to the altered expression of KLF4, MSI2, and miR-10b and differential changes in Erk, Akt, and PTEN signaling. We conclude that Sdc-1 knockdown differentially affects HA metabolism in luminal and triple-negative breast cancer model cell lines and impacts the stem phenotype, cell survival, and angiogenic factors.     

Iron, folic acid and vitamin B12 deficiencies related to anemia in adolescents from a region with a high incidence of congenital malformations in Venezuela

Since in recent years for certain age groups, the main cause of anemia is not iron deficiency, we intended to study the effect of iron, folic acid and vitamin B12 deficiencies on anemia prevalence in adolescents from Venezuela. One hundred adolescents aged between 12 and 19 years participated in the study. Each subject was interviewed about antecedents and habits and a physical examination and a 24-hour food recall questionnaire were performed. From a blood sample, hemoglobin and hematocrit concentrations were determined and serum was separated for quantification of ferritin, folic acid and vitamin B12 concentrations. Prevalence of anemia was 78% and for iron, folic acid and vitamin B12 deficiencies were 34.66, 90.9 and 18.18%, respectively. From anemic cases, 35.89% presented iron deficiency, while 91.02% presented folic acid deficiency. Only 19.23% of adolescents with anemia presented also vitamin B12 deficiency, but all the cases with vitamin B12 deficiency, were anemic. Simultaneous iron and folic acid deficiencies affected 30.76% of anemic cases. The high prevalence of deficiencies found in this work could be explained by insufficient intake and inadequate food habits. The prevalence of anemia was associated to folic acid deficiency rather than to iron deficiency, due to the high prevalence of folic acid deficiency. The high prevalence of nutritional deficiencies found in this work, especially regarding folic acid deficiency, require immediate interventions.     

Range Unit‐Root (RUR) Tests: Robust against Nonlinearities,Error Distributions,Structural Breaks and Outliers

Abstract. Since the seminal paper by Dickey and Fuller in 1979, unit‐root tests have conditioned the standard approaches to analysing time series with strong serial dependence in mean behaviour, the focus being placed on the detection of eventual unit roots in an autoregressive model fitted to the series. In this paper, we propose a completely different method to test for the type of long‐wave patterns observed not only in unit‐root time series but also in series following more complex data‐generating mechanisms. To this end, our testing device analyses the unit‐root persistence exhibited by the data while imposing very few constraints on the generating mechanism. We call our device the range unit‐root (RUR) test since it is constructed from the running ranges of the series from which we derive its limit distribution. These nonparametric statistics endow the test with a number of desirable properties, the invariance to monotonic transformations of the series and the robustness to the presence of important parameter shifts. Moreover, the RUR test outperforms the power of standard unit‐root tests on near‐unit‐root stationary time series; it is invariant with respect to the innovations distribution and asymptotically immune to noise. An extension of the RUR test, called the forward–backward range unit‐root (FB‐RUR) improves the check in the presence of additive outliers. Finally, we illustrate the performances of both range tests and their discrepancies with the Dickey–Fuller unit‐root test on exchange rate series.     

The biological leaching of an auriferous pyrite ore

The oxidation of an auriferous pyrite ore sample was evaluated in biological leaching experiments for subsequent gold recovery via cyanidation. In batch cultures, organisms derived from the mine site oxidized pyrite and ferrous iron at pH values as low as pH 0.6. The recovery of gold was variable in shake flask experiments. In stirred tank bioreactor leaching, gold recovery was proportional to the extent of iron dissolution by bioleaching. The leaching of arsenic from the sample was also directly proportional to iron dissolution.     

Estimating the Economic Value of Landscape Losses Due to Flooding by Hydropower Plants in the Chilean Patagonia

This paper presents a contingent valuation study concerning landscape impacts generated by the construction of one dam (Baker 1) of the HIDROAYSEN hydropower project located in the Chilean Patagonia. A survey was used to collect information about citizens’ opinions towards the hydropower project in four major cities in Chile. Specifically, a One-and-One-Half-Bound (OOHB) willingness to pay eliciting format was applied to capture citizens’ WTP. The economic loss, associated to the landscape impacts for people living in urban areas of the country, is found to be approximately US$ 205 million, which is nearly 28% of the total investment. Our results also show that the cities’ distance from the dam affects citizens’ willingness to pay.     

Parallel Time and Quantifier Prefixes

We characterize the amount of alternation between blocks of Boolean quantifiers (having both existential and universal), blocks of real existential quantifiers, and blocks of real universal quantifiers that can be decided in parallel polynomial time over the reals. We do so under the assumption that blocks have a uniform bound on their size, both for the case of this bound to be polynomial and constant. On the way towards this characterization we prove a real version of Savitch’s Theorem.     

Bond calibration method for Young’s modulus determination in the discrete element method framework

A new methodology for the calibration of bond microparameters in rocks represented by a package of joined random spherical particles in the discrete element method (DEM) framework is presented. Typically, calibration is achieved through a trial-and-error procedure using several DEM simulations of uniaxial compressive tests (UCTs). The bond calibration model (BCM) does not need a time-dependent UCT-DEM simulation to establish the relation between the microproperties of the bond and the macroproperties of the rock specimen. The BCM uses matrices to describe the interaction forces exerted by bonds and, by means of an assembly process similar to the finite element method, it can describe the complex network of bonds, enabling the model to capture small variations in particle size and bond distribution as demonstrated in this work. In this work, the BCM is presented and compared with UCT simulations performed using Esys Particle software. Multiple simulations are done with constant bond properties and different particle size ratios (\(D_{MAX}/D_{MIN})\) that cause small variations in the specimen’s Young’s modulus; these variations are well captured by the BCM with an error of <10%.     

Generating blogs out of product catalogues: An MDE approach

Blogs can be used as a conduit for customer opinions and, in so doing, building communities around products. We attempt to realise this vision by building blogs out of product catalogues. Unfortunately, the immaturity of blog engines makes this endeavour risky. This paper presents a model-driven approach to face this drawback. This implies the introduction of (meta)models: the catalogue model, based on the standard Open Catalog Format, and blog models, that elaborate on the use of blogs as conduits for virtual communities. Blog models end up being realised through blog engines. Specifically, we focus on two types of engines: a hosted blog platform and a standalone blog platform, both in Blojsom. However, the lack of standards in a broad and constantly evolving blog-engine space, hinders both the portability and the maintainability of the solution. Hence, we resort to the notion of “abstract platform” as a way to depart from the peculiarities of specific blog engines. Additionally, the paper measures the reuse gains brought by MDE in comparison with the manual coding of blogs.     

Indoor robot gardening: design and implementation

This paper describes the architecture and implementation of a distributed autonomous gardening system with applications in urban/indoor precision agriculture. The garden is a mesh network of robots and plants. The gardening robots are mobile manipulators with an eye-in-hand camera. They are capable of locating plants in the garden, watering them, and locating and grasping fruit. The plants are potted cherry tomatoes enhanced with sensors and computation to monitor their well-being (e.g. soil humidity, state of fruits) and with networking to communicate servicing requests to the robots. By embedding sensing, computation, and communication into the pots, task allocation in the system is de-centrally coordinated, which makes the system scalable and robust against the failure of a centralized agent. We describe the architecture of this system and present experimental results for navigation, object recognition, and manipulation as well as challenges that lie ahead toward autonomous precision agriculture with multi-robot teams.