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While it has been established that course-based undergraduate research experiences (CUREs) lead to student benefits, it is less clear what aspects of CUREs lead to such gains. In this study, we aimed to understand the effect of students analyzing their own data, compared with students analyzing data that had been collected by professional scientists. We compared the experiences of students in a CURE investigating whether the extinction risk status of terrestrial mammals and birds is associated with their ecological traits. Students in the CURE were randomly assigned to analyze either data that they had collected or data previously collected by professional scientists. selleck inhibitor All other aspects of the student experience were designed to be identical. We found that students who analyzed their own data showed significantly greater gains in scientific identity and emotional ownership than students who analyzed data collected by professional scientists.Social media is an increasingly important professional tool for scientists. In particular, scientists use their social media profiles to communicate science and build communities with like-minded scientists and nonscientists. These networks include journalists who can amplify social media science communication, disseminating it to new audiences on- and offline. Our experience with an outreach project where Peeps marshmallows were inoculated with diverse fungi, which we called #FungalPeeps, has demonstrated that these networks can be an effective conduit between researchers and high school students. Following popular science journalism, #FungalPeeps, a project initiated at West Virginia University, inspired a mycology research project in Notre Dame High School in San Jose, California. Herein, we describe how this connection between academia, journalists, and the high school classroom happened, and how everyone involved benefited from this educational collaboration. We further suggest ways that modern social media networks could be leveraged to incorporate more such practical learning experiences into progressive science curricula to better cultivate young STEM scientists.Identification of causal relations among variables is central to many scientific investigations, as in regulatory network analysis of gene interactions and brain network analysis of effective connectivity of causal relations between regions of interest. Statistically, causal relations are often modeled by a directed acyclic graph (DAG), and hence that reconstruction of a DAG's structure leads to the discovery of causal relations. Yet, reconstruction of a DAG's structure from observational data is impossible because a DAG Gaussian model is usually not identifiable with unequal error variances. In this article, we reconstruct a DAG's structure with the help of interventional data. Particularly, we construct a constrained likelihood to regularize intervention in addition to adjacency matrices to identify a DAG's structure, subject to an error variance constraint to further reinforce the model identifiability. Theoretically, we show that the proposed constrained likelihood leads to identifiable models, thus correct reconstruction of a DAG's structure through parameter estimation even with unequal error variances. Computationally, we design efficient algorithms for the proposed method. In simulations, we show that the proposed method enables to produce a higher accuracy of reconstruction with the help of interventional observations.Pseudomyxoma peritonei with pleural extension is very rare. Dissemination in the pleural cavity can be trans diaphragmatic or hematogenous. Appendicular and ovarian mucinous tumors are the most often involved. Imaging plays an important role in the diagnosis which is confirmed histologically. We report the case of a pseudomyxoma peritonei and pleurii in a 55-year-old female patient who underwent surgery for mucinous adenocarcinoma of the ovary. This diagnosis must be suggested when there is subpleural nodular thickening associated with pseudomyxoma peritonei.We report a case of ependymoma of the broad ligament occurring in a 21-year-old woman. CT and MRI findings showed a 40-mm-diameter, well-demarcated cystic mass with a lobulated solid component in the right pelvis. The solid component showed heterogeneous intermediate signal intensity on T2-weighted image and prolonged mild contrast enhancement. The tumor was resected and confirmed as ependymoma based on the histologic findings along with its immunohistochemical profile. To our knowledge, this is the first report of an adnexal ependymoma describing the precise radiological characteristics that resembled those of borderline or malignant epithelial ovarian tumors.We report a case of primary breast lymphoma which was incidentally detected in a 71 year-old-female while investigating for pulmonary embolism with Computed tomography angiograph (CTA) of the chest. Primary breast lymphoma has no specific imaging features however may have better prognosis than breast carcinoma and management is non-surgical.Iniencephaly (IE) is a rare neural tube malformation involving severe head retroflexion and deformity of the spine. IE is typically accompanied with other congenital abnormalities and carrying a poor fetal prognosis. This report presents radiological findings in a rare case of IE associated with multiple malformations of the skull, spine, face, heart, and body. A 44-year-old pregnant female underwent an obstetric ultrasound examination on the 26th week of gestation followed by fetal magnetic resonance imaging on the 36th week. Imaging revealed complex developmental anomalies, which led to the diagnosis of IE with a large cervical meningocele, occipital bone defect, spina bifida of the cervical vertebrae, multiple malformed vertebra, deformed face, coarctation of the aortic arch, and hypoplastic lungs. Based on these findings, a decision to terminate pregnancy was made. Pathological examination of the fetus showed close agreement with imaging. The presented case underscores the importance of multimodal imaging for clinical decision making in the management of complex neural tube malformations.
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