Causal inference at the population level

Three elements are needed to formalize a causal quantity at the population level: response, treatment, and the causal element, which are introduced here by notation. Inclusion of two essential causal assumptions, the monitoring and illumination assumptions, in a function distinguishes causal from association analyses. The discussion provides insight into causal inference

From classical mendelian randomization to causal networks for systematic integration of multi-omics

The number of studies with information at multiple biological levels of granularity, such as genomics, proteomics, and metabolomics, is increasing each year, and a biomedical questaion is how to systematically integrate these data to discover new biological mechanisms that have the potential to elucidate the processes of health and disease. Causal frameworks, such as Mendelian randomization (MR), provide a foundation to begin integrating data for new biological discoveries. Despite the growing number of MR applications in a wide variety of biomedical studies, there are few approaches for the systematic analysis of omic data. The large number and diverse types of molecular components involved in complex diseases interact through complex networks, and classical MR approaches targeting individual components do not consider the underlying relationships. In contrast, causal network models established in the principles of MR offer significant improvements to the classical MR framework for understanding omic data. Integration of these mostly distinct branches of statistics is a recent development, and we here review the current progress. To set the stage for causal network models, we review some recent progress in the classical MR framework. We then explain how to transition from the classical MR framework to causal networks. We discuss the identification of causal networks and evaluate the underlying assumptions. We also introduce some tests for sensitivity analysis and stability assessment of causal networks. We then review practical details to perform real data analysis and identify causal networks and highlight some of the utility of causal networks. The utilities with validated novel findings reveal the full potential of causal networks as a systems approach that will become necessary to integrate large-scale omic data

Evaluation of Apical Transportation in Root Canals Prepared with Hand File and Two Rotary Files by Cone Beam Computed Tom ography

The purpose of the mechanical cleaning of the root canal is to create a conical shape for 3D filling of the canal area. Excessive dentin removal from one side of the canal, as compared to other parts located at an equal distance to the longitudinal axis of the tooth, causes an error called the canal transportation. In this study, the canal transportation was evaluated by hand K-flexo file Mtwo and,Dia-pt rotary file using Cone Beam Computed Tomography (CBCT). This is an Ex-vivo study conducted on 60 extracted first molars. Root curvature was measured by Schneider's method. Preparation was performed in three groups of 20 with manual and Mtwo and Dia-pt files. CBCT images were prepared before and after clearing the canals. Data were analyzed using SPSS 18 Software. Based on the results of the kruskal wallis test, there are differences between the three files in the 2 and 3 mm sections (respectively (p = 0.01) (p = 0.01)). However, there is no difference in the cross-section of 2.5 mm based on kruskal wallis test (p = 0.16). The results of this study indicate that the channel displacement in the Mtwo system is the least. And this system is better than K-Flexo file and Dia-pt in following the shape of the canal and creating a conical canal with the least deviation from the channel

Design of a Distribution Network in a Multi-product, Multi-period Green Supply Chain System Under Demand Uncertainty

ABSTRACT: This paper proposes a novel fuzzy mathematical model for a distribution network design problem in a multi-product, multi-period, multi-echelon, multi-plant, multi-retailer, multi-mode of transportation green supply chain system. The three purposes of the model are to minimise total network cost, maximise net profit per capita for each human resource, and diminish CO2 emission throughout the network. P-hub median location with multiple allocations is used for locating the distribution centres. One scenario is designed for fuzzy customer demands with a trapezoidal membership function. Furthermore, the model determines the design of the network (selecting the optimum numbers, locations of plants, and distribution centres to open), finding the best strategy for material transportation through the network with the availability of different transportation modes, the capacities level of the facilities (plants or distribution centres (DCs)), and the number of outsourced products. Finally, all uncertain customer demands for all product types can be satisfied based on the methods mentioned above. This multi-objective mixed-integer non-linear mathematical model is solved by NSGA-II, MOPSO and a hybrid meta-heuristic algorithm. The results show that NSGA-II is the exclusive algorithm that obtains the best result according to the evaluation criteria

Explanation of Value conflict resolution experiences\' of medical teachers in Kashan Medical University: A Qualitative content analysis

Introduction: The values of individuals that orient their preferences and behaviors are not the same; this can lead to disagreements and be the basis of value conflicts. The present study aimed to analyze the value conflict resolution experiences and how to deal with the value conflicts among the faculty members. Methods: In this qualitative study, a semi-structured interview was carried out with purposeful and then snowball sampling with 11 teachers from Kashan University of Medical Sciences for data saturation. Then, the content of the interviews were analyzed by Grahamman 2004 content analysis. Results: The research participants included 6 males and 5 females who were specialists, Ph.D and Masters Degree graduates with a working experience of 3.5 years to 29 years. The final model derived from the value conflict resolution experience was in the form of 5 themes and main categories: 1. Components of the experiences of organizational value conflicts 2. Experiences of value conflicts with learners 3. Ranking of values in the instructors 4. The components of the type of conflict of value 5. Value conflict solving styles. Conclusion: Based on the results of the study, the components and styles used to solve the value conflicts that were experienced by the teachers of Kashan University of Medical Sciences can serve as a model for teaching and empowering professors as well as adopting effective strategies for dealing with value conflicts and management. Contradictions are used in educational settings. &nbsp