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There is much debate concerning students' evaluation of teaching and several academics discredit the validity and reliability of student comments. Student feedback would be a good source of information for academics to improve their teaching, while earlier studies indicate that the academics do not always make use of student feedback in their teaching development. Their perception on the applicability of the student feedback can be related to teachers' attitude towards student feedback and their teaching conceptions. Furthermore, it may influence their motivation and efforts to participate in pedagogical trainings and willingness to improve their teaching. The research question for the current study was: What are the relationships between the academics' conceptions of teaching and participation in pedagogical courses and their willingness and ability to apply student evaluation of teaching feedback to enhance teaching practice? Forty two academics were interviewed and interviews were analysed using qualitative content analysis. As the result of the analysis three profiles of academics' were formed: 1) academics with consistent attitude, 2) ambivalent attitude and 3) arrogant attitude towards student evaluation of teaching feedback. The study revealed how academics respond to such feedback and how they use it to develop their teaching depends on academics' conceptions of teaching, attitude towards student feedback and participation in pedagogical courses.

Imaging-based differentiation between glioblastoma (GB) and brain metastases (BM) remains challenging. Our aim was to evaluate the performance of 3D-convolutional neural networks (CNN) to address this binary classification problem. T1-CE, T2WI, and FLAIR 3D-segmented masks of 307 patients (157 GB and 150 BM) were generated post resampling, co-registration normalization and semi-automated 3D-segmentation and used for internal model development. Subsequent external validation was performed on 59 cases (27 GB and 32 BM) from another institution. Four different mask-sequence combinations were evaluated using area under the curve (AUC), precision, recall and F1-scores. Diagnostic performance of a neuroradiologist and a general radiologist, both without and with the model output available, was also assessed. 3D-model using the T1-CE tumor mask (TM) showed the highest performance [AUC 0.93 (95% CI 0.858–0.995)] on the external test set, followed closely by the model using T1-CE TM and FLAIR mask of peri-tumoral region (PTR) [AUC of 0.91 (95% CI 0.834–0.986)]. Models using T2WI masks showed robust performance on the internal dataset but lower performance on the external set. Both neuroradiologist and general radiologist showed improved performance with model output provided [AUC increased from 0.89 to 0.968 (p = 0.06) and from 0.78 to 0.965 (p = 0.007) respectively], the latter being statistically significant. 3D-CNNs showed robust performance for differentiating GB from BMs, with T1-CE TM, either alone or combined with FLAIR-PTR masks. Availability of model output significantly improved the accuracy of the general radiologist. • 3-dimensional CNN models can differentiate GB from BM with high accuracy. • The best performing models used T1-CE images, either alone or combined with FLAIR images. • The model output significantly improved the accuracy of the general radiologist. [ABSTRACT FROM AUTHOR]

The absence of published reference values for multilayer-specific strain measurement using cardiac magnetic resonance (CMR) in young healthy individuals limits its use. This study aimed to establish normal global and layer-specific strain values in healthy children and young adults using a deformable registration algorithm (DRA). A retrospective study included 131 healthy children and young adults (62 males and 69 females) with a mean age of 16.6 ± 3.9 years. CMR examinations were conducted using 1.5T scanners, and strain analysis was performed using TrufiStrain research prototype software (Siemens Healthineers, Erlangen, Germany). Global and layer-specific strain parameters were extracted from balanced Steady-state free precession cine images. Statistical analyses were conducted to evaluate the impact of demographic variables on strain measurements. The peak global longitudinal strain (LS) was −16.0 ± 3.0%, peak global radial strain (RS) was 29.9 ± 6.3%, and peak global circumferential strain (CS) was −17.0 ± 1.8%. Global LS differed significantly between males and females. Transmural strain analysis showed a consistent pattern of decreasing LS and CS from endocardium to epicardium, while radial strain increased. Basal-to-apical strain distribution exhibited decreasing LS and increasing CS in both global and layer-specific analysis. This study uses DRA to provide reference values for global and layer-specific strain in healthy children and young adults. The study highlights the impact of sex and age on LS and body mass index on RS. These insights are vital for future cardiac assessments in children, particularly for early detection of heart diseases. [ABSTRACT FROM AUTHOR]

Cardiac magnetic resonance imaging is crucial for diagnosing cardiovascular diseases, but lengthy postprocessing and manual segmentation can lead to observer bias. Deep learning (DL) has been proposed for automated cardiac segmentation; however, its effectiveness is limited by the slice range selection from base to apex. In this study, we integrated an automated slice range classification step to identify basal to apical short-axis slices before DL-based segmentation. We employed publicly available Multi-Disease, Multi-View & Multi-Center Right Ventricular Segmentation in Cardiac MRI data set with short-axis cine data from 160 training, 40 validation, and 160 testing cases. Three classification and seven segmentation DL models were studied. The top-performing segmentation model was assessed with and without the classification model. Model validation to compare automated and manual segmentation was performed using Dice score and Hausdorff distance and clinical indices (correlation score and Bland-Altman plots). The combined classification (CBAM-integrated 2D-CNN) and segmentation model (2D-UNet with dilated convolution block) demonstrated superior performance, achieving Dice scores of 0.952 for left ventricle (LV), 0.933 for right ventricle (RV), and 0.875 for myocardium, compared to the stand-alone segmentation model (0.949 for LV, 0.925 for RV, and 0.867 for myocardium). Combined classification and segmentation model showed high correlation (0.92-0.99) with manual segmentation for biventricular volumes, ejection fraction, and myocardial mass. The mean absolute difference (2.8-8.3 mL) for clinical parameters between automated and manual segmentation was within the interobserver variability range, indicating comparable performance to manual annotation. Integrating an initial automated slice range classification step into the segmentation process improves the performance of DL-based cardiac chamber segmentation. [ABSTRACT FROM AUTHOR]

Public archives are repositories of human memory and history, which collect, preserve, and provide access to the records and documents creating a bridge between the past, present, and future. Archives are dynamic structures that can be interpreted as knowledge hubs, with channels of information flowing in them, activities performed within the "black box" of the institution invisible for outsiders, and channels to disseminate information for groups that they serve. These channels develop and are designed under the impact of several factors. In this article we present six factors that have shaped the development and functioning of the Estonian Folklore Archives. We first illustrate the impact of these factors, browsing through the historical periods of Estonian folkloristics. Successively, the articles of the current volume on various aspects of tradition archives are introduced and presented within the framework of the hub conception, and the relevant impact factors are highlighted. The article demonstrates that ideological framework, public expectations, institutional status, research paradigms, individual incentives of the people in charge, and (developments in) technological equipment constantly shape the content and operation of tradition archives in various time periods and circumstances. [ABSTRACT FROM AUTHOR]

Cardiovascular computed tomography (CCT) is rated appropriate by published guidelines for the initial evaluation and follow up of congenital heart disease (CHD) and is an essential modality in cardiac imaging programs for patients of all ages. However, no recommended core competencies exist to guide CCT in CHD imaging training pathways, curricula development, or establishment of a more formal educational platform. To fill this gap, a group of experienced congenital cardiac imagers, intentionally inclusive of adult and pediatric cardiologists and radiologists, was formed to propose core competencies fundamental to the expert-level performance of CCT in pediatric acquired and congenital heart disease and adult CHD. The 2020 SCCT Guideline for Training Cardiology and Radiology Trainees as Independent Practitioners (Level II) and Advanced Practitioners (Level III) in Cardiovascular Computed Tomography (1) for adult imaging were used as a framework to define pediatric and CHD-specific competencies. Established competencies will be immediately relevant for advanced cardiac imaging fellowships in both cardiology and radiology training pathways. Proposed future steps include radiology and cardiology society collaboration to establish provider certification levels, training case-volume recommendations, and continuing medical education (CME) requirements for expert-level performance of CCT in pediatric and adult CHD. [ABSTRACT FROM AUTHOR]

Variation is a core feature of folklore that plays a part in configuring the processes of folkloric communication, transmission and creativity. Computational analysis of large folklore collections offers new outlooks on the study of variation. The article explores the nature of folkloric variation on the basis of folk song and fairy tale text corpora from the Estonian Folklore Archives. Our enquiry into regional variation in Estonian folk song showed different patterns of geographic variation for metre, repertoire and language. To investigate further the possibilities to disassemble the components of variation we turned to a smaller corpus of fairy tale texts from the distinct Seto language community. The results of stylometric analysis of fairy tales collected within the close language community as a rule found that word usage patterns in stories told by the same storytellers were closer to each other than stories with the same content (i.e. tale types). However, other factors, such as collectors' individual styles, recording time, length of text, and storyteller's place of origin contributed notably to similarity as per stylometric scores. The study has shown that the individual features and aspects of such a complex phenomenon as folklore can follow its own variation patterns. Computational analysis of the variation in large text corpora helps us get a better understanding of the functioning of variation, and the processes of folkloric creation. However, the layers of folkloric variation are not that easy to disassemble, one must be aware of the biases in text corpora and keep in mind the effect of the linguistic variation on the results. [ABSTRACT FROM AUTHOR]

Copyright of SHILAP Revista de Lepidopterologia is the property of Sociedad Hispano-Luso-Americana de Lepidopterologia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Cotadutide, a peptide co-agonist at the glucagon-like peptide-1 (GLP-1) and glucagon (GCG) receptors, has demonstrated robust improvements in body weight, glycemia, and hepatic fat fraction (HFF) in patients living with obesity and type 2 diabetes mellitus. In PROXYMO, a 19-week randomized double-blind placebo-controlled trial, the safety and efficacy of cotadutide (600 μg, 300 μg) or placebo were evaluated in 74 participants with biopsy-proven noncirrhotic metabolic dysfunction-associated steatohepatitis (MASH) with fibrosis. Analyses were performed using intent-to-treat and modified intent-to-treat population data. Dose- and time-dependent improvements in HFF, alanine aminotransferase (ALT), and aspartate aminotransferase (AST), markers of liver health, and metabolic parameters were observed with significant improvements after 19 weeks with 600 μg ([least squares] mean difference vs placebo, [95% confidence interval] for absolute HFF: –5.0% [–8.5 to –1.5]; ALT: –23.5 U/L [–47.1 to –1.8]; AST: –16.8 U/L [–33.0 to –0.8]). Incidences of any grade treatment-emergent adverse events (TEAEs) were 91.7%, 76.9%, and 37.5% with cotadutide 600 μg, 300 μg, and placebo, respectively. The majority were gastrointestinal, mild to moderate in severity, and generally consistent with other incretins at this stage of development. TEAEs leading to treatment discontinuation were 16.7%, 7.7%, and 4.2% with cotadutide 600 μg, 300 μg, and placebo, respectively. PROXYMO provides preliminary evidence for the safety and efficacy of GLP-1/GCG receptor co-agonism in biopsy-proven noncirrhotic MASH with fibrosis, supporting further evaluation of this mechanism in MASH. Clinical Trial registration number: NCT04019561. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this study was to analyze the prevalence and significance of incidental findings on computed tomography pulmonary angiography (CTPA) studies and to assess the diagnostic yield of CTPA in identifying an alternate diagnosis to pulmonary embolism (PE) on PE negative exams.Methods: All patients who had a CTPA exam for PE evaluation between Jan 2016 and Dec 2018 with a negative PE result were included in the study. A total of 2083 patients were identified. We retrospectively queried the electronic medical record and the radiology report and recorded the following: Age, Sex, BMI, Patient location and Incidental findings. The incidental findings were classified into type 1 (Alternate diagnosis other than PE which could explain the patient's symptoms), type 2 (non-emergent findings which needed further work up) and type 3 findings (non-emergent findings which did not need further work up). Logistic regression analysis was performed to determine what factors affected the probability of finding a type 1 incidental (alternate diagnosis) or a type 2 incidental.Results: 74.5% of the patients in our study had at least one incidental finding. Type 1 incidental findings (alternate diagnosis to PE) were found in 864 patients (41.5%). The most common type 1 finding was pneumonia followed by fluid overload. Male sex, increased age and lower BMI were significantly associated with increased odds of a type 1 incidental(p < 0.05). Similarly, all the patient locations had significantly different odds of finding a type-1 incidental, with ICU having the highest odds, followed by inpatient, ED and outpatient locations (p < 0.05). 563 patients (27%) had at least one type 2 incidental findings and the most common type 2 findings were progressive lung malignancy/ metastatic disease and new pulmonary nodule. Increased age was significantly associated with the probability of a type 2 finding (p < 0.05).Conclusions: CTPA may suggest an alternative diagnosis to pulmonary embolism in approximately 40% of the patients with a negative study. The probability of finding an alternate diagnosis (type 1 incidental) is higher in elderly patients and in patients referred from ICU and inpatient units. [ABSTRACT FROM AUTHOR]

The article discusses a study that proposes an initial nomological network surrounding information and communication technology (ICT) and corruption and theorizes the salient role of basic national institutions and national stakeholder service systems into the mechanisms through which e-government affects corruption. It provides mechanisms by which corruption permeates from the institutional level to the functional service level in a nation and explains how e-government can alleviate it.

Erdheim–Chester disease (ECD) is a disease of non-Langerhans cell histiocyte multisystemic proliferation. The pathogenesis is related to accumulation of histiocytes across the body, leading to multiple organ failure, and thus necessitating an early diagnosis. In all ECD cases, BRAF and RAS mutations are critical. Clinical manifestations affect individuals between the fourth and seventh decades of life. The most common symptoms reported are central nervous system involvement with functional disability, and bone pain with osteosclerosis of long bones. Other reported symptoms are skin involvement with xanthelasma, diabetes insipidus, cardiovascular involvement with pericardial effusion and tamponade, perivascular thickening, and right atrial and atrioventricular grove infiltration, leading to heart failure. Females may develop galactorrhoea due to deposition in the pituitary gland, with or without menstrual irregularities. Only few publications address the cardiac MRI findings of ECD. The authors present a case of cardiac involvement of ECD and associated cardiac MRI findings. The patient presented with multisystemic disease with bone pain, diplopia, cardiac arrythmia, and dyspnoea.