Yoxas/statistical_literacy huggingface dataset:
Phenomenon: The increase in clinical and teaching workload has brought enormous pressure to clinical teachers. Clinical teachers play an extremely important role in the quality of higher medical education and the cultivation of medical talents. However, few studies have examined the attitudes and practices of clinical teachers regarding the role of teachers in China. This study aimed to investigate clinical teachers' perceptions about their roles and current practices at affiliated hospitals of medical universities in China. Approach: Responses from 312 Chinese clinical teachers were included in the analyses. The data were collected using the questionnaires of perception and practice regarding the role of teachers which consisted of 12 items rated on a 5-point Likert scale, ranging from 1 (strongly disagree) to 5 (strongly agree), and scored by calculating the mean. The data were analyzed using the Statistical Package for Social Sciences, version 22.0 (IBM SPSS Corp). Findings: The mean score of perception of clinical teachers regarding the role of teachers was 4.51 (SD = 0.72), and the mean score of practice was 3.69 (SD = 1.17). Multivariable binary logistic regression model showed that undertaking very few/few clinical teaching workload, 'thinking it is my obligation to carry out teaching work seriously' and 'thinking it is my duty to train medical talents' were not only significant determinants of good perception but also good practice. Additionally, 'thinking hospital attached great importance to clinical teaching' was the significant determinant of good perception. Insights: Chinese clinical teachers demonstrate less positive perception and practice regarding the roles of teacher than clinical teachers in developed countries. Affiliated hospitals of medical universities should hold training sessions regularly and take targeted intervention measures to enhance clinical teachers' perception and practice regarding the roles of teacher.
Phenotyping analysis that includes time course is useful for understanding the mechanisms and clinical management of postoperative delirium. However, postoperative delirium has not been fully phenotyped. Hypothesis-free categorization of heterogeneous symptoms may be useful for understanding the mechanisms underlying delirium, although evidence is currently lacking. Therefore, we aimed to explore the phenotypes of postoperative delirium following invasive cancer surgery using a data-driven approach with minimal prior knowledge. We recruited patients who underwent elective invasive cancer resection. After surgery, participants completed 5 consecutive days of delirium assessments using the Delirium Rating Scale-Revised-98 (DRS-R-98) severity scale. We categorized 65 (13 questionnaire items/day × 5 days) dimensional DRS-R-98 scores using unsupervised machine learning (K-means clustering) to derive a small set of grouped features representing distinct symptoms across all participants. We then reapplied K-means clustering to this set of grouped features to delineate multiple clusters of delirium symptoms. Participants were 286 patients, of whom 91 developed delirium defined according to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, criteria. Following the first K-means clustering, we derived four grouped symptom features: (1) mixed motor, (2) cognitive and higher-order thinking domain with perceptual disturbance and thought content abnormalities, (3) acute and temporal response, and (4) sleep-wake cycle disturbance. Subsequent K-means clustering permitted classification of participants into seven subgroups: (i) cognitive and higher-order thinking domain dominant delirium, (ii) prolonged delirium, (iii) acute and brief delirium, (iv) subsyndromal delirium-enriched, (v) subsyndromal delirium-enriched with insomnia, (vi) insomnia, and (vii) fit. We found that patients who have undergone invasive cancer resection can be delineated using unsupervised machine learning into three delirium clusters, two subsyndromal delirium clusters, and an insomnia cluster. Validation of clusters and research into the pathophysiology underlying each cluster will help to elucidate the mechanisms of postoperative delirium after invasive cancer surgery.
Phenylketonuria is an inherited metabolic disorder that leads to neurobehavioral dysfunction. The main treatment is a low-phenylalanine diet and/or the cofactor tetrahydrobiopterin. Regular outpatient follow-up care and measurement of the phenylalanine levels in the blood are required. We aimed to analyze the economic burden of phenylketonuria on families and the state. The patients with phenylketonuria were divided into three groups according to their treatment: a low-phenylalanine diet group (n = 50), a tetrahydrobiopterin group (n = 44), and a group taking tetrahydrobiopterin together with the diet (n = 25). A comparative cost analysis was carried out. The annual economic burden to the state was calculated to average EUR 18,801 ± 15,345 and was lowest in the diet group, then in the tetrahydrobiopterin group, and highest in the tetrahydrobiopterin + diet group (p < 0.001). Out-of-pocket costs amounted to EUR 1531 ± 1173 per year, and indirect losses averaged EUR 2125 ± 1930 per year for all families. The economic loss was significantly lower in the families taking tetrahydrobiopterin than in the other groups (p = 0.001). The combined use of medical nutrition and BH4 treatments has been shown to increase the economic burden on the state. Reimbursing low-protein products and increasing the number of patients eligible for financial allowances may reduce the economic burden on families.
Philanthropic donations are an increasingly important funding source for academic medical centers. Minimal published data is available about factors that influence alumni donations to residency programs. We performed a cross-sectional analysis of a single-site dermatology and combined internal medicine-dermatology residency programs to assess factors impacting alumni donations. Donors tended to have graduated less recently (only 20% graduating after 2010) and practice in the same region of their alma mater (50%). Respondents preferred funds be allocated to resident needs over needs of medical students. Strategically engaging senior alumni and offering fund allocation opportunities could increase philanthropy, with alumni perceptions of the residency program warranting further investigation for their impact on donation decisions.
Philosophers and scientists alike argue that wonder-that emotion or state of consciousness in which one's attention is fixed on phenomena beyond one's comprehension-is the central virtue and driving force of all education. As in general education, wonder is central to all aspects of academic medicine's tripartite mission; a sense of wonder fuels the delivery of humanized patient care, sparks scientific discoveries, and supports engagement in lifelong learning. Despite its importance throughout medicine, developing a capacity for wonder among physicians has not been a stated goal of medical education, and innovative methods to foster a capacity for wonder have not been explored. There is a growing interest in the arts and humanities in medical education, and evidence suggests that these can support the development of a diverse array of clinically relevant skills and attitudes (including close observation, critical thinking, empathy, and tolerance for ambiguity) in medical learners across the learning continuum. However, even the potential of these methods to support a capacity for wonder has not yet been fully explored. In this article, the authors explore how one of the most widely used and studied arts-based learning activities in medical education, Visual Thinking Strategies, can help develop a capacity for wonder among physicians. They illustrate how Visual Thinking Strategies support the central elements of wonder-based pedagogy (i.e., exploration, improvisation, imagination, personal interest, and the ethos of educators) previously developed in education theory.
Phonological awareness and alphabet knowledge are fundamental building blocks for literacy development. We identified preschoolers with persistent delays in these skills and evaluated the efficacy of a supplemental curriculum to remediate deficits in early literacy skills. Using a cluster design, 21 classrooms were randomly assigned to early literacy versus language intervention conditions. Sixty children identified through fall semester assessments of phonological awareness and alphabet knowledge were enrolled in small-group instruction. Teachers completed eLearning modules, used a digital platform to enter data and facilitate data-based decision making, received practice-based coaching, and delivered 12 weekly units of an early literacy curriculum. Comparison teachers delivered similarly administered small-group language instruction. Large effects were evident for letter sounds, phoneme segmentation, first sound, and first sound fluency measures (d = 0.92, 4.77, 1.15, and 1.50, respectively), and nonsignificant, small effects for letter naming and blending measures (d = 0.26 and 0.27). This early literacy intervention package had practical benefits, with 90% of experimental group preschoolers exceeding the phonemic awareness benchmark for beginning kindergarten compared to 45% in the comparison group, for example. Providing preschool teachers with tools and support for implementing a tiered approach to early literacy intervention holds promise for producing impressive gains in skills required for children to succeed in later schooling.
Phonological processing skills, such as phonological awareness, are known predictors of reading acquisition in alphabetic languages with varying degrees of orthographic complexity. However, the role of multi-letter-sound knowledge, an important foundation for early reading development, in supporting reading fluency development remains to be determined. This study examined whether two core foundational skills, phonemic awareness and grapheme sounding, have a predictive role in reading fluency development in an intermediate-depth orthography. The participants were 62 children learning to read in European Portuguese, and they were longitudinally assessed on phonemic awareness, complex grapheme sounding, and reading fluency (decoding, word, and text) from Grade 2 to Grade 3. The results showed that grapheme sounding predicted reading fluency development controlled for nonverbal intelligence and vocabulary, short-term verbal memory, and phonemic awareness. Grapheme sounding plays a prominent role in predicting reading fluency outcomes, whereas phonemic awareness (both accuracy and time per correct item) did not contribute to any of the three types of reading fluency. The fact that grapheme-sounding predicted reading fluency is likely due to complex grapheme-phoneme correspondences being required to achieve proficient reading. These findings provide insights into the cognitive processes underlying reading development in intermediate-depth orthographies and have implications for early literacy instruction.
Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.
Photokeratoconjunctivitis (PKC) is primarily caused by welding. However, inappropriate use of germicidal lamps, which have been widely used following the COVID-19 outbreak, can also cause PKC. Our goal in this study was to investigate the incidence of and changes in the causes of PKC during the coronavirus 2019 (COVID-19) pandemic. We conducted a single-center, retrospective observational study. The health records of patients who visited the emergency department in a tertiary care hospital from January 1, 2018-December 31, 2021 and were diagnosed with PKC, were reviewed. We then conducted an analysis to compare the characteristics of PKC before and after COVID-19 began and the features of PKC caused by welding and germicidal lamps. There were 160 PKC cases with a clear etiology before the COVID-19 pandemic and 147 cases during the COVID-19 pandemic. No significant differences in age and gender were detected between the two groups. The incidence of PKC induced by the use of germicidal lamps during the COVID-19 pandemic was significantly higher (10.2%) than the incidence before the pandemic (3.1%). The ratio of females to males in the germicidal lamp subgroup was significantly higher than the ratio in the welding subgroup. Limitations included incomplete information due to the retrospective nature of the study, underestimation of incidence, and possible recall bias. In the era of COVID-19, clinicians should be aware of the hazards of germicidal lamps. Although the COVID-19 pandemic seems to show signs of easing, new infectious diseases that require protective measures could still emerge in the future. Therefore, injuries related to germicidal lamps deserve more public health attention.
Photon counting CT (PCCT) holds promise for mitigating metal artifacts and can produce virtual mono-energetic images (VMI), while maintaining temporal resolution, making it a valuable tool for characterizing the heart. This study aimed to evaluate and optimize PCCT for cardiac imaging in patients during left ventricular assistance device (LVAD) therapy by conducting an in-depth objective assessment of metal artifacts and visual grading. Various scan and reconstruction settings were tested on a phantom and further evaluated on a patient acquisition to identify the optimal protocol settings. The phantom comprised an empty thoracic cavity, supplemented with heart and lungs from a cadaveric lamb. The heart was implanted with an LVAD (HeartMate 3) and iodine contrast. Scans were performed on a PCCT (NAEOTOM Alpha, Siemens Healthcare). Metal artifacts were assessed by three objective methods: Hounsfield units (HU)/SD measurements (DiffHU and SDARTIFACT), Fourier analysis (AmplitudeLowFreq), and depicted LVAD volume in the images (BloomVol). Radiologists graded metal artifacts and the diagnostic interpretability in the LVAD lumen, cardiac tissue, lung tissue, and spinal cord using a 5-point rating scale. Regression and correlation analysis were conducted to determine the assessment method most closely associated with acquisition and reconstruction parameters, as well as the objective method demonstrating the highest correlation with visual grading. Due to blooming artifacts, the LVAD volume fluctuated between 27.0 and 92.7 cm3. This variance was primarily influenced by kVp, kernel, keV, and iMAR (R2 = 0.989). Radiologists favored pacemaker iMAR, 3 mm slice thickness, and T3D keV and kernel Bv56f for minimal metal artifacts in cardiac tissue assessment, and 110 keV and Qr40f for lung tissue interpretation. The model adequacy for DiffHU SDARTIFACT, AmplitueLowFreq, and BloomVol was 0.28, 0.76, 0.29, and 0.99 respectively for phantom data, and 0.95, 0.98, 1.00, and 0.99 for in-vivo data. For in-vivo data, the correlation between visual grading (VGSUM) and DiffHU SDARTIFACT, AmplitueLowFreq, and BloomVol was -0.16, -0.01, -0.48, and -0.40 respectively. We found that optimal scan settings for LVAD imaging involved using 120 kVp and IQ level 80. Employing T3D with pacemaker iMAR, the sharpest allowed vascular kernel (Bv56f), and VMI at 110 keV with kernel Qr40 yields images suitable for cardiac imaging during LVAD-therapy. Volumetric measurements of the LVAD for determination of the extent of blooming artifacts was shown to be the best objective method to assess metal artifacts.
Phylogenetic studies now routinely require manipulating and summarizing thousands of data files. For most of these tasks, currently available software requires considerable computing resources and substantial knowledge of command-line applications. We develop an ultrafast and memory-efficient software, SEGUL, that performs common phylogenomic dataset manipulations and calculates statistics summarizing essential data features. Our software is available as standalone command-line interface (CLI) and graphical user interface (GUI) applications, and as a library for Rust, R and Python, with possible support of other languages. The CLI and library versions run native on Windows, Linux and macOS, including Apple ARM Macs. The GUI version extends support to include mobile iOS, iPadOS and Android operating systems. SEGUL leverages the high performance of the Rust programming language to offer fast execution times and low memory footprints regardless of dataset size and platform choice. The inclusion of a GUI minimizes bioinformatics barriers to phylogenomics while SEGUL's efficiency reduces economic barriers by allowing analysis on inexpensive hardware. Our support for mobile operating systems further enables teaching phylogenomics where access to computing power is limited.
Phylogenetic trees describe relationships between extant species, but beyond that their shape and their relative branch lengths can provide information on broader evolutionary processes of speciation and extinction. However, currently many of the most widely used macro-evolutionary models make predictions about the shapes of phylogenetic trees that differ considerably from what is observed in empirical phylogenies. Here, we propose a flexible and biologically plausible macroevolutionary model for phylogenetic trees where times to speciation or extinction events are drawn from a Coxian phase-type (PH) distribution. First, we show that different choices of parameters in our model lead to a range of tree balances as measured by Aldous' [Formula: see text] statistic. In particular, we demonstrate that it is possible to find parameters that correspond well to empirical tree balance. Next, we provide a natural extension of the [Formula: see text] statistic to sets of trees. This extension produces less biased estimates of [Formula: see text] compared to using the median [Formula: see text] values from individual trees. Furthermore, we derive a likelihood expression for the probability of observing an edge-weighted tree under a model with speciation but no extinction. Finally, we illustrate the application of our model by performing both absolute and relative goodness-of-fit tests for two large empirical phylogenies (squamates and angiosperms) that compare models with Coxian PH distributed times to speciation with models that assume exponential or Weibull distributed waiting times. In our numerical analysis, we found that, in most cases, models assuming a Coxian PH distribution provided the best fit.
Phylogenetics has moved into the era of genomics, incorporating enormous volumes of data to study questions at both shallow and deep scales. With this increase in information, phylogeneticists need new tools and skills to manipulate and analyze these data. To facilitate these tasks and encourage reproducibility, the community is increasingly moving toward automated workflows. Here we present pipesnake, a phylogenomics pipeline written in Nextflow for the processing, assembly, and phylogenetic estimation of genomic data from short-read sequences. pipesnake is an easy to use and efficient software package designed for this next era in phylogenetics. pipesnake is publicly available on GitHub at https://github.com/AusARG/pipesnake and accompanied by documentation and a wiki/tutorial.
Physical activity (PA) and physical fitness (PF) are important markers of health status in children and adolescents in different ethnicities. In this study, we aimed to compare the PA and PF indicators between Tibetan and Han children and adolescents. Children and adolescents of 4-9 grades were recruited in Shigatse (n = 963) and Shanghai (n = 2,525) respectively. The information related to demographic, PA, and PF was collected via a self-reported questionnaire. PA was assessed through the participation of moderate to vigorous PA (MVPA), muscle-strengthening exercise (MSE) and organized sport participation (OSP). PF was estimated using the International Fitness Scale containing components of overall fitness, cardiorespiratory fitness, speed and agility, muscular strength and flexibility. Han (mean age = 13.45 ± 3.3 years; 49.7% girls) and Tibet (mean age = 13.8 ± 2.5 years; 48.3% girls) children and adolescents from Shanghai and Shigatse completed the questionnaire survey. It was revealed that Tibetan students had higher MVPA, MSE and OSP than children and adolescents of Han ethnicity (p < 0.01, small to medium effect size). A relatively higher percentage of student in Shanghai did not participate in any form of PA. On the other hand, less Tibetan students thought their PF indicators including overall fitness, cardiorespiratory fitness, speed and agility, muscular strength and flexibility were poor or very poor than their counterparts of Han ethnicity (p < 0.01, small to medium effect size). Tibetan children and adolescents have higher levels of PA and PF in comparison to their Han counterparts. More children and adolescents of Han ethnicity engage in no PA and think their PF indicators were poor.
Physical activity (PA) is a promising intervention for disease modification and symptom management in multiple sclerosis (MS); however, there is a lack of research focusing on PA behavior change interventions for persons newly diagnosed with MS. Such PA behavior change interventions should be developed based on a strong empirical foundation of understanding the behavior and its determinants (ie, what to target for changes to occur). To that end, this qualitative study examined factors explaining PA in persons newly diagnosed with MS and identified potential targets for future behavior change intervention development based on the Capability-Opportunity-Motivation-Behavior (COM-B) model. Twenty individuals diagnosed with MS within the past 2 years underwent one-on-one semistructured interviews using questions developed based on the COM-B model. Data were analyzed using reflective thematic analysis, and the identified themes were then mapped with the COM-B model. Factors explaining PA in the study sample were identified across the COM-B components. The typical factors include knowledge and skills to sufficiently engage in PA with appropriate approaches, ability to adapt and navigate through new environmental and social difficulties after diagnosis, and motivation resulting from a combination of factors, such as outcome expectation, belief of capabilities, role/identity, reinforcement, and emotions. The COM-B model was applied successfully in this study to understand PA behavior and identify potential targets for behavior change in individuals newly diagnosed with MS. Future behavior change interventions should consider addressing these factors to generate effective PA behavior change in this population.