142 research outputs found
Inference on a stochastic two-compartment model in tumor growth
A continuous-time model that incorporates several key elements in tumor dynamics is analyzed. More precisely, the form of proliferating and quiescent cell lines comes out from their relations with the whole tumor mass, giving rise to a two-dimensional diffusion process, generally time non-homogeneous. This model is able to include the effects of the mutual interactions between the two subpopulations. Estimation of the rates of the two subpopulations based on some characteristics of the involved diffusion processes is discussed when longitudinal data are available. To this aim, two procedures are presented. Some simulation results are developed in order to show the validity of these procedures as well as to compare them. An application to real data is finally presented
Dialogical interactions mediated by technology in mathematics education
This paper discusses the results of a research[1] that integrates Digital Interactive Storytelling (DIST), competence-oriented mathematical activities, and argumentation called DIST-M. The general aim is to support a reflective knowledge of mathematical concepts by implementing a digital educational device based on collaborative and dialogical activities proposed by researchers. Within a dialogical dimension of interactions (Bakhtin, 1981), argumentative practice is considered a social activity, where the acquisition and elaboration of new knowledge take place within a social space with multiple interlocutors in a dynamic process. The participants are engaged in constructing and negotiating mathematical meanings within a specific context. This dialogical approach to argumentation tends to create an authentic argumentative culture that is a system of implicit and explicit rules where the exchanges and interactions among participants require a joint elaboration of new meanings, within a given mathematical context, through a dialogical exchange. Learning and development result from a dialogical negotiation process during which new knowledge is developed and those already possessed are re-organized and systematized (Bakhtin, 1981; Vygotskij, 1978). In the current pandemic circumstances, technologies are the main tools to uphold the educational processes. Despite the fact that the DIST-M was implemented and tested before the Covid-19 era, its epistemic bases of dialogism mediated by technology could significantly keep alive the dialogic interaction in educational settings that have been heavily affected by the social distancing and promote mathematical thinking. The articles focus on the United Nations Sustainable Development Goal n. 4,” Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all.”
[1] The research is funded by the Italian Ministry of Education, University and Research under the National Project “Digital Interactive Storytelling in Mathematics: a competence-based social approach”, PRIN 2015, Prot. 20155NPRA5
Parameter estimation in continuous stochastic volatility models
Continuous-time di usion processes are often used in literature to
model dynamics of nancial markets. In such kinds of models a rel-
evant role is played by the variance of the process. So assumptions
on the functional form of such variance have to be made in order to
analyse the distribution of the resulting process and to make inference
on the model. In this paper the variance is also modelled by means of
a di usion process. This comes out as continuous time approximation
of a GARCH(1; 1) process. Inference on the parameters and properties
of the involved estimators are discussed under di erent choices of the
frequency data. Simulations on the model are also performed
Study of a general growth model
We discuss a general growth curve including several parameters, whose choice leads to a variety of models including the classical cases of Malthusian, Richards, Gompertz, Logistic and some their generalizations. The advantage is to obtain a single mathematically tractable equation from which the main characteristics of the considered curves can be deduced. We focus on the effects of the involved parameters through both analytical results and computational evaluations
Electrochemical and morphological layer-by-layer characterization of electrode interfaces during a label-free impedimetric immunosensor build-up: The case of ochratoxin A
Abstract In this paper, we provide an in-depth electrochemical characterization of a label-free impedimetric immunosensor for rapid detection of ochratoxin A. The sensor was based on a carbodiimide-mediated amide coupling reaction to immobilize a specific ochratoxin A antibody onto 4-mercaptobenzoic acid-modified commercial screen-printed gold electrode. Different variables affecting the performance of the developed sensor were optimized. Cyclic voltammetry and electrochemical impedance spectroscopy were used to analyse modifications of the interfacial properties occurring at each step of the biosensor assembly. The free electrode surface area, the diffusion coefficient, the peak-to-peak separation, the heterogeneous electron transfer constant, and charge transfer resistance have been calculated and compared. The decrease of charge transfer resistance values was linearly proportional to the ochratoxin A concentration in the range of 0.37– 2.86 ng/mL, with a detection limit of 0.19 ng/mL, a limit of quantification of 0.40 ng/mL, very good selectivity, reproducibility, and storage stability in the absence of antifouling agents. Surface morphology and topographic data at each step of the immunosensor assembly were studied by Atomic Force Microscopy, which also provided information on the specific binding of ochratoxin A. Finally, contact angle measurements revealed the hydrophilicity evolution of the surface during sensor assembly enabling OTA binding
Digital Storytelling and Mathematical Thinking: An Educational Psychology Embrace
This article proposes Digital Storytelling as an education model that combines science, narrative thinking and art. This model has been implemented in Italian school settings over recent years. After a short introduction of the theoretical foundations of narrative thinking in the history of Educational Psychology, the paper focuses on Digital Storytelling as a co-constructive educational method that uses digital technologies for promoting an active, situated, meaningful and reflexive learning process. The proposed intervention in the Italian settings adds the artistic digital component (the use of avatar, comics and science fiction) to the Digital Storytelling systems. The set of implemented activities, as well as the individual and group actions taken, promote both the cognitive and emotional aspects of the learning process. The findings show that Digital Storytelling, spiced with artistic features, prompts the engagement of students in learning activities and offers a platform to enhance behavioural, emotional and cognitive commitment in mathematics education
Inference on an heterocedastic Gompertz tumor growth model
We consider a non homogeneous Gompertz diffusion process whose parameters are modified by generally time-dependent exogenous factors included in the infinitesimal moments. The proposed model is able to describe tumor dynamics under the effect of anti-proliferative and/or cell death-induced therapies. We assume that such therapies can modify also the infinitesimal variance of the diffusion process. An estimation procedure, based on a control group and two treated groups, is proposed to infer the model by estimating the constant parameters and the time-dependent terms. Moreover, several concatenated hypothesis tests are considered in order to confirm or reject the need to include time-dependent functions in the infinitesimal moments. Simulations are provided to evaluate the efficiency of the suggested procedures and to validate the testing hypothesis. Finally, an application to real data is considered
Ligand-based chemoinformatic discovery of a novel small molecule inhibitor targeting CDC25 dual specificity phosphatases and displaying in vitro efficacy against melanoma cells
CDC25 phosphatases are important regulators of the cell cycle and represent promising targets for anticancer drug discovery. We recently identified NSC 119915 as a new quinonoid CDC25 inhibitor with potent anticancer activity. In order to discover more active analogs of NSC 119915, we performed a range of ligand-based chemoinformatic methods against the full ZINC drug-like subset and the NCI lead-like set. Nine compounds (3, 5?9, 21, 24, and 25) were identified with Ki values for CDC25A, -B and -C ranging from 0.01 to 4.4 ?M. One of these analogs, 7, showed a high antiproliferative effect on human melanoma cell lines, A2058 and SAN. Compound 7 arrested melanoma cells in G2/M, causing a reduction of the protein levels of CDC25A and, more consistently, of CDC25C. Furthermore, an intrinsic apoptotic pathway was induced, which was mediated by ROS, because it was reverted in the presence of antioxidant N-acetyl-cysteine (NAC). Finally, 7 decreased the protein levels of phosphorylated Akt and increased those of p53, thus contributing to the regulation of chemosensitivity through the control of downstream Akt pathways in melanoma cells. Taken together, our data emphasize that CDC25 could be considered as a possible oncotarget in melanoma cells and that compound 7 is a small molecule CDC25 inhibitor that merits to be further evaluated as a chemotherapeutic agent for melanoma, likely in combination with other therapeutic compounds
Droplet digital PCR assay for quantifying of CALR mutant allelic burden in myeloproliferative neoplasms
Ruxolitinib – better prognostic impact in low-intermediate 1 risk score: evaluation of the ‘rete ematologica pugliese’ (REP) in primary and secondary myelofibrosis
We evaluated ruxolitinib in 65 patients with myelofibrosis according to age, sex, time of diagnosis, grade of fibrosis, prognostic score risk, Janus kinase (JAK) status, primary or secondary myelofibrosis, previous treatment, and dosage. Outcome measures were response rate, time to response, duration of response, and event-free survival and survival. Kaplan and Meier curves show a significant difference in event-free survival according to the prognostic score, in favor of patients with low int1 (p = 0.0009). The Cox stepwise model confirmed the result, the int2 high-risk score being the most powerful negative independent parameter (0.001), followed by JAK (0.008); other parameters, such as diagnosis more than 5 years earlier, grade III–IV fibrosis, and ruxolitinib dose have a negligible impact. Time to response was shorter (p = 0.001) in primary myelofibrosis. In conclusion, ruxolitinib is effective, with a better outcome in patients with a low-int1 risk score. This may suggest considering an earlier administration in the disease course
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