A Three-day CLIL Workshop : what was learned and produced

現在多くの日本の大学では、グローバルな教育内容と環境を促進することが火急の課題である。岡山大学では英語教育の質の向上と授業科目の英語での提供の２つに取り組んでいるが、その実践においてCLIL（内容言語統合型学習）が有用であると考えられる。また日本の高等教育機関において、CLIL を既に実践あるいは導入を検討している教育関係者と経験やアイデアを共有し、ネットワークを作って今後の情報交換を行うことも非常に重要である。そこで岡山大学では2016 年2 月にフィンランドから２名の講師を招き、３日間のCLIL ワークショップを開催した。この論文では４大学の参加者４名がワークショップで紹介された２つの大学の異なったCLIL モデルについて報告する。またワークショップで行った様々なアクティビティを通して参加者が学び取ったことや成果についても記述する

Community support for injured patients:A scoping review and narrative synthesis

Background: Community-based peer support (CBPS) groups have been effective in facilitating access to and retention in the healthcare system for patients with HIV/AIDS, cancer, diabetes, and other communicable and non-communicable diseases. Given the high incidence of morbidity that results from traumatic injuries, and the barriers to reaching and accessing care for injured patients, community-based support groups may prove to be similarly effective in this population.Objectives: The objective of this review is to identify the extent and impact of CBPS for injured patients.Eligibility: We included primary research on studies that evaluated peer-support groups that were solely based in the community. Hospital-based or healthcare-professional led groups were excluded.Evidence: Sources were identified from a systematic search of Medline / PubMed, CINAHL, and Web of Science Core Collection.Charting methods: We utilized a narrative synthesis approach to data analysis.Results: 4,989 references were retrieved; 25 were included in final data extraction. There was a variety of methodologies represented and the groups included patients with spinal cord injury (N = 2), traumatic brain or head injury (N = 7), burns (N = 4), intimate partner violence (IPV) (N = 5), mixed injuries (N = 5), torture (N = 1), and brachial plexus injury (N = 1). Multiple benefits were reported by support group participants; categorized as social, emotional, logistical, or educational benefits.Conclusions: Community-based peer support groups can provide education, community, and may have implications for retention in care for injured patients

Unraveling the Determinants of Protrusion Formation

A computerized morphometric classification technique based on latent factors reveals major protrusion classes: factors 4, 5, and 7. Previous work showed that factor 4 represented filopodia, 5 the distribution of lamellar cytoplasm, and 7 a blunt protrusion. We explore the relationship of focal contact (FC) characteristics and their integrated actin cables to factors values. The results show that FC maturation/cytoskeletal integration affects factor 5, because FC elongation/integration was correlated with its values. On the contrary, 7 values decreased with maturation, so cable or FC size or their integration must be restricted to form these protrusions. Where integration did occur, the cables showed distinctive size and orientation, as indicated by correlation of 7 values with FC shape. Results obtained with myosin inhibitors support the interpretation that a central, isometric, contractile network puts constraints on both factor 5 and 7 protrusions. We conclude that cells establish functional domains by rearranging the cytoskeleton

A scoping review on the use of machine learning in research on social determinants of health: Trends and research prospects

Background: Machine learning (ML) has spread rapidly from computer science to several disciplines. Given the predictive capacity of ML, it offers new opportunities for health, behavioral, and social scientists. However, it remains unclear how and to what extent ML is being used in studies of social determinants of health (SDH). Methods: Using four search engines, we conducted a scoping review of studies that used ML to study SDH (published before May 1, 2020). Two independent reviewers analyzed the relevant studies. For each study, we identified the research questions, Results, data, and algorithms. We synthesized our findings in a narrative report. Results: Of the initial 8097 hits, we identified 82 relevant studies. The number of publications has risen during the past decade. More than half of the studies (n = 46) used US data. About 80% (n = 66) utilized surveys, and 70% (n = 57) employed ML for common prediction tasks. Although the number of studies in ML and SDH is growing rapidly, only a few studies used ML to improve causal inference, curate data, or identify social bias in predictions (i.e., algorithmic fairness). Conclusions: While ML equips researchers with new ways to measure health outcomes and their determinants from non-conventional sources such as text, audio, and image data, most studies still rely on traditional surveys. Although there are no guarantees that ML will lead to better social epidemiological research, the potential for innovation in SDH research is evident as a result of harnessing the predictive power of ML for causality, data curation, or algorithmic fairness

Assessing Strength of Evidence of Appropriate Use Criteria for Diagnostic Imaging Examinations

Objective For health information technology tools to fully inform evidence-based decisions, recommendations must be reliably assessed for quality and strength of evidence. We aimed to create an annotation framework for grading recommendations regarding appropriate use of diagnostic imaging examinations. Methods The annotation framework was created by an expert panel (clinicians in three medical specialties, medical librarians, and biomedical scientists) who developed a process for achieving consensus in assessing recommendations, and evaluated by measuring agreement in grading the strength of evidence for 120 empirically selected recommendations using the Oxford Levels of Evidence. Results Eighty-two percent of recommendations were assigned to Level 5 (expert opinion). Inter-annotator agreement was 0.70 on initial grading (κ = 0.35, 95% CI, 0.23-0.48). After systematic discussion utilizing the annotation framework, agreement increased significantly to 0.97 (κ = 0.88, 95% CI, 0.77-0.99). Conclusions A novel annotation framework was effective for grading the strength of evidence supporting appropriate use criteria for diagnostic imaging exams

Inhibition of neutrophil apoptosis after severe trauma is NFkappabeta dependent

BACKGROUND: Systemic inflammation may inhibit neutrophil (PMN) apoptosis and promote multiple organ dysfunction syndrome. We hypothesize that severe trauma causes dysregulation of PMN apoptosis. METHODS: Neutrophils were isolated from trauma patients (24-72 hours after injury; n = 16) and controls (healthy volunteers) and incubated for 18 hours. In separate experiments, control cells were treated +/- the nuclear factor kappa beta (NFkappabeta) inhibitor pyrrolidinithiocarbamate then incubated with 25% patient or control plasma. Apoptosis was quantified by enzyme-linked immunosorbent assay for histone-associated DNA and annexin V fluorescence-activated cell sorter. NFkappabeta activation was determined by Western blot for phosphorylated I kappabeta. RESULTS: Apoptosis was inhibited in trauma patient PMN. Neutrophil apoptosis correlated with multiple organ dysfunction syndrome score, Acute Physiology and Chronic Health Evaluation II, and platelet count. Patient plasma inhibited apoptosis and induced phosphorylation of I kappabeta in control cells. Inhibition of PMN apoptosis by patient plasma was blocked by pretreatment with pyrrolidinithiocarbamate. CONCLUSION: NFkappabeta-dependent inhibition of neutrophil apoptosis occurs after trauma. Early inhibition of PMN apoptosis is dependent on the magnitude of injury

The impact of socio-economic factors on parental non-adherence to the Ponseti protocol for clubfoot treatment in low- and middle-income countries: A scoping review.

The Ponseti treatment is considered the gold standard for clubfoot globally, but requires strong engagement from parents. The aim of this review is to assess the impact of socio-economic factors on the presence of drop-out, relapse or non-compliance during Ponseti treatment in low and middle-income countries (LMICs).info:eu-repo/semantics/publishe