Good practices for the development of budget impact models at regional level

Introduction: The present work aims to discuss the current scenario of procedures and regulations regarding budget impact analysis/models (BIA/BIM) at regional level in Italy and to provide a standardized approach and detailed recommendations for developing these analyses. Method: A systematic review of the literature was conducted in order to collect existing guidelines or specific regional procedures for budget impact analysis in Italy. All the records were analysed in qualitative terms according to a pre-specified analytical framework, based on the ISPOR BIA guidelines. At the end of the analysis, a consensus questionnaire was developed to establish agreed approaches and to provide possible solutions to any critical issues. A list of 39 statements was developed. The survey was distributed to 69 experts who rated their level of agreement with each statement on a 5-point Likert scale. Consensus was predefined as more than 66% of the panel agreeing/disagreeing with any given statement. Results: Sisty-nine experts answered the questionnaire; a total of 30/39 statements achieved consensus. There was agreement on most of the statements. Time horizon to consider and costs were the issues on which no agreement was found. The results allowed the working group to define a list of good practices. Conclusion: While the structure and development of BIM are now well-known and well-applied at national level, there remains a great diversity of management of BIM tools at regional level. Consensus was reached among participating experts, as to the main characteristics, determinants and features of regional BIA/BIM in the perspective of the Italian payer

Implant Placement in Patients under Treatment with Rivaroxaban: A Retrospective Clinical Study

The management of patients under treatment with Direct Oral Anticoagulants (DOACs) has led clinicians to deal with two clinical issues, such as the hemorrhagic risk in case of non-interruption or the risk of thromboembolism in case of suspension of the treatment. The primary aim of this retrospective study was to evaluate the incidence of perioperative bleeding events and healing complications in patients who were under treatment with Rivaroxaban and who received dental implants and immediate prosthetic restoration. Patients treated with Rivaroxaban (Xarelto 20 mg daily) and who needed implant rehabilitation were selected. Four to six implants were placed in mandibular healed sites or fresh extraction sockets. All patients, in agreement with their physicians, interrupted the medication for 24 h and received implants and immediate restorations. Twelve patients and 57 implants were analyzed in the study. No major postoperative bleeding events were reported. Three patients (25%) presented slight immediate postoperative bleeding controlled with compression only. The implant and prosthetic survival rate were both 100% after 1 year. Within the limitations of this study, multiple implant placement with an immediate loading can be performed without any significant complication with a 24 h discontinuation of Rivaroxaban, in conjunction with the patient’s physician

Coordinated Pulses of mRNA and of Protein Translation or Degradation Produce EGF-Induced Protein Bursts

Protein responses to extracellular cues are governed by gene transcription, mRNA degradation and translation, and protein degradation. In order to understand how these time-dependent processes cooperate to generate dynamic responses, we analyzed the response of human mammary cells to the epidermal growth factor (EGF). Integrating time-dependent transcript and protein data into a mathematical model, we inferred for several proteins their pre-and post-stimulus translation and degradation coefficients and found that they exhibit complex, time-dependent variation. Specifically, we identified strategies of protein production and degradation acting in concert to generate rapid, transient protein bursts in response to EGF. Remarkably, for some proteins, for which the response necessitates rapidly decreased abundance, cells exhibit a transient increase in the corresponding degradation coefficient. Our model and analysis allow inference of the kinetics of mRNA translation and protein degradation, without perturbing cells, and open a way to understanding the fundamental processes governing time-dependent protein abundance profiles

Predictive Toxicology of Cobalt Nanoparticles and Ions: Comparative In Vitro Study of Different Cellular Models Using Methods of Knowledge Discovery from Data.

International audienc

Predictive Toxicology of cobalt ferrite nanoparticles: comparative in-vitro study of different cellular models using methods of knowledge discovery from data.

International audienceBACKGROUND: Cobalt-ferrite nanoparticles (Co-Fe NPs) are attractive for nanotechnology-based therapies. Thus, exploring their effect on viability of seven different cell lines representing different organs of the human body is highly important. METHODS: The toxicological effects of Co-Fe NPs were studied by in-vitro exposure of A549 and NCIH441 cell-lines (lung), precision-cut lung slices from rat, HepG2 cell-line (liver), MDCK cell-line (kidney), Caco-2 TC7 cell-line (intestine), TK6 (lymphoblasts) and primary mouse dendritic-cells. Toxicity was examined following exposure to Co-Fe NPs in the concentration range of 0.05 -1.2 mM for 24 and 72 h, using Alamar blue, MTT and neutral red assays. Changes in oxidative stress were determined by a dichlorodihydrofluorescein diacetate based assay. Data analysis and predictive modeling of the obtained data sets were executed by employing methods of Knowledge Discovery from Data with emphasis on a decision tree model (J48). RESULTS: Different dose-response curves of cell viability were obtained for each of the seven cell lines upon exposure to Co-Fe NPs. Increase of oxidative stress was induced by Co-Fe NPs and found to be dependent on the cell type. A high linear correlation (R2=0.97) was found between the toxicity of Co-Fe NPs and the extent of ROS generation following their exposure to Co-Fe NPs. The algorithm we applied to model the observed toxicity belongs to a type of supervised classifier. The decision tree model yielded the following order with decrease of the ranking parameter: NP concentrations (as the most influencing parameter), cell type (possessing the following hierarchy of cell sensitivity towards viability decrease: TK6 > Lung slices > NCIH441 > Caco-2 = MDCK > A549 > HepG2 = Dendritic) and time of exposure, where the highest-ranking parameter (NP concentration) provides the highest information gain with respect to toxicity. The validity of the chosen decision tree model J48 was established by yielding a higher accuracy than that of the well-known "naive bayes" classifier. CONCLUSIONS: The observed correlation between the oxidative stress, caused by the presence of the Co-Fe NPs, with the hierarchy of sensitivity of the different cell types towards toxicity, suggests that oxidative stress is one possible mechanism for the toxicity of Co-Fe NPs