Copyright for education: a case study of Palestine

Palestine is a poor and disrupted territory and education is vital to its future prosperity and wellbeing. Copyright—which regulates access to information—can at times have a negative effect on education; even more so in least developed countries like Palestine. The aim of this thesis is to explain how copyright and education can function more effectively in the Palestinian context to bring about transformational change and meaningful development. To this end, the thesis (after explaining the Palestinian legal and social context) highlights the common ground between copyright and education and challenges them to work together, rather than against each other. It analyses copyright law in Palestine and how it might be reformed to provide better educational outcomes. Acknowledging that law reform is difficult to achieve, the thesis suggests that a more pragmatic and viable option is to employ strategic copyright management, or what is known as voluntary mechanisms (meaning the copyright owner agrees for various reasons to their material being shared through open access). In outlining this option the thesis provides a detailed roadmap for how Palestine can reap the rewards of voluntary mechanisms

DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.

Motivation: Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. Results: We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using 5-repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs. Availability and implementation: The data and code are provided at https://bitbucket.org/RSO24/ddr/. Contact: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online

DTi2Vec: Drug-target interaction prediction using network embedding and ensemble learning.

Drug-target interaction (DTI) prediction is a crucial step in drug discovery and repositioning as it reduces experimental validation costs if done right. Thus, developing in-silico methods to predict potential DTI has become a competitive research niche, with one of its main focuses being improving the prediction accuracy. Using machine learning (ML) models for this task, specifically network-based approaches, is effective and has shown great advantages over the other computational methods. However, ML model development involves upstream hand-crafted feature extraction and other processes that impact prediction accuracy. Thus, network-based representation learning techniques that provide automated feature extraction combined with traditional ML classifiers dealing with downstream link prediction tasks may be better-suited paradigms. Here, we present such a method, DTi2Vec, which identifies DTIs using network representation learning and ensemble learning techniques. DTi2Vec constructs the heterogeneous network, and then it automatically generates features for each drug and target using the nodes embedding technique. DTi2Vec demonstrated its ability in drug-target link prediction compared to several state-of-the-art network-based methods, using four benchmark datasets and large-scale data compiled from DrugBank. DTi2Vec showed a statistically significant increase in the prediction performances in terms of AUPR. We verified the novel predicted DTIs using several databases and scientific literature. DTi2Vec is a simple yet effective method that provides high DTI prediction performance while being scalable and efficient in computation, translating into a powerful drug repositioning tool

Child mental health in Jordanian orphanages: effect of placement change on behavior and caregiving

Background: To assess the mental health and behavioral problems of children in institutional placements in Jordan to inform understanding of current needs, and to explore the effects of placement change on functioning and staff perceptions of goodness-of-fit. Methods: An assessment was completed of 134 children between 1.5? 12 years-of-age residing in Jordanian orphanages. The Child Behavior Checklist was used to assess prevalence rates of problems across externalizing and internalizing behavior and DSM-IV oriented subscales. Also included was caregiver perceived goodness-of-fit with each child, caregiving behavior, and two placement change-clock variables; an adjustment clock measuring time since last move, and an anticipation clock measuring time to next move. Results: 28% were in the clinical range for the internalizing domain on the CBCL, and 22% for the externalizing domain. The children also exhibited high levels of clinical range social problems, affective disorder, pervasive developmental disorder, and conduct problems. Internalizing problems were found to decrease with time in placement as children adjust to a prior move, whereas externalizing problems increased as the time to their next age-triggered move drew closer, highlighting the anticipatory effects of change. Both behavioral problems and the change clocks were predictive of staff perceptions of goodness-of-fit with the children under their care. Conclusions: These findings add to the evidence demonstrating the negative effects of orphanage rearing, and highlight the importance of the association between behavioral problems and child-caregiver relationship pathways including the timing of placement disruptions and staff perceptions of goodness-of-fit

EHR Visual Overlay Promises to Improve Hypertension Guideline Implementation

Background: Primary care management of essential hypertension (HTN) has become increasingly challenging since recently published guidelines integrate atherosclerotic cardiovascular disease (ASCVD) risk stratification into decision making. Our objective was to measure whether overlay of visualdecision support (VDS) with standard electronic health record (EHR) platform improves guideline-based treatment, and reduces time burden associated with EHR use, in management of essential HTN. Methods: This was a quality improvement project. We interviewed primary care physicians and tasked each with two simulated patient encounters for HTN: (1) using standard EHR to guide treatment, and (2) using VDS to guide treatment. The VDS included graphical blood pressure (BP) trends, target BP with recommended interventions, ASCVD risk score, and information on the patient’s social determinants of health. We assessed whether treatment selection was congruent with guidelines and tracked time physicians consulted the EHR. Results: We evaluated 70 case simulations in total. Use of VDS compared to usual EHR was associated with: higher proportion of correct guideline prescribing (94% vs. 60%, p\u3c0.01), more ASCVD risk determination (100% vs. 23, p\u3c0.01), and more correct BP target identification (97% vs. 60%, p\u3c0.01). Time clinicians spent consulting the EHR fell an average of 121 seconds with use of VDS (p\u3c0.01). On a 10-point scale, clinicians rated the VDS 9.2 vs. 5.9 (p\u3c0.01) for ease of gathering necessary information to treat HTN. Conclusions: The integration video decision support tools to standard EHR can reduce physician time spent per patient encounter, while increasing adherence to guidelines and improving patient outcomes. Further testing in clinical practice is indicated.https://scholarlycommons.henryford.com/merf2019qi/1009/thumbnail.jp

Self-medication practice among undergraduate medical students of a Saudi tertiary institution

Purpose: To assess the knowledge, attitude and magnitude of self-medication among medical students of Jazan University, Jazan, Saudi Arabia.Methods: A cross-sectional, self-administered questionnaire-based study was conducted among undergraduate medical students of Jazan University, Jazan, Saudi Arabia. A total of 300 students were selected by random sampling.Results: Self-medication practice was highly prevalent among the medical students, with 87 % reporting that they indulge in it. Self-medication was more prevalent among female students than male. Sedatives were the most common drugs used by students for self-medication (58 %). The most common reason adduced for self-medication practice was their belief that they have sufficient information, previous experience, and the experience of others, such as family members and colleagues, with regard to the drugs. A huge proportion (84.5 %) of the respondents agreed that selfmedication could be harmful and is associated with adverse effects, while 52.6 % stated that they would not advise other persons to indulge in self-medication.Conclusion: Self-medication is prevalent among third-year medical students of Jazan University in Saudi Arabia. Although the students exhibited sufficient awareness of self-medication, the findings highlight the need for intervention programmes regarding the practice of self-medication.Keywords: Self-medication, Prevalence, Awareness, Sedatives, Medical student

Derivation and validation of the ED-SAS score for very early prediction of mortality and morbidity with acute pancreatitis: a retrospective observational study

BACKGROUND: Existing scoring systems to predict mortality in acute pancreatitis may not be directly applicable to the emergency department (ED). The objective of this study was to derive and validate the ED-SAS, a simple scoring score using variables readily available in the ED to predict mortality in patients with acute pancreatitis. METHODS: This retrospective observational study was performed based on patient data collected from electronic health records across 2 independent health systems; 1 was used for the derivation cohort and the other for the validation cohort. Adult patients who were eligible presented to the ED, required hospital admission, and had a confirmed diagnosis of acute pancreatitis. Patients with chronic or recurrent episodes of pancreatitis were excluded. The primary outcome was 30-day mortality. Analyses tested and derived candidate variables to establish a prediction score, which was subsequently applied to the validation cohort to assess odds ratios for the primary and secondary outcomes. RESULTS: The derivation cohort included 599 patients, and the validation cohort 2011 patients. Thirty-day mortality was 4.2 and 3.9%, respectively. From the derivation cohort, 3 variables were established for use in the predictive scoring score: ≥2 systemic inflammatory response syndrome (SIRS) criteria, age \u3e 60 years, and SpO2 \u3c 96%. Summing the presence or absence of each variable yielded an ED-SAS score ranging from 0 to 3. In the validation cohort, the odds of 30-day mortality increased with each subsequent ED-SAS point: 4.4 (95% CI 1.8-10.8) for 1 point, 12.0 (95% CI 4.9-29.4) for 2 points, and 41.7 (95% CI 15.8-110.1) for 3 points (c-statistic = 0.77). CONCLUSION: An ED-SAS score that incorporates SpO2, age, and SIRS measurements, all of which are available in the ED, provides a rapid method for predicting 30-day mortality in acute pancreatitis

Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation

BACKGROUND: Primary care management of hypertension under new guidelines incorporates assessment of cardiovascular disease risk and commonly requires review of electronic health record (EHR) data. Visual analytics can streamline the review of complex data and may lessen the burden clinicians face using the EHR. This study sought to assess the utility of a visual analytics dashboard in addition to EHR in managing hypertension in a primary care setting. METHODS: Primary care physicians within an urban, academic internal medicine clinic were tasked with performing two simulated patient encounters for HTN management: the first using standard EHR, and the second using EHR paired with a visual dashboard. The dashboard included graphical blood pressure trends with guideline-directed targets, calculated ASCVD risk score, and relevant medications. Guideline-appropriate antihypertensive prescribing, correct target blood pressure goal, and total encounter time were assessed. RESULTS: We evaluated 70 case simulations. Use of the dashboard with the EHR compared to use of the EHR alone was associated with greater adherence to prescribing guidelines (95% vs. 62%, p\u3c0.001) and more correct identification of BP target (95% vs. 57%, p\u3c0.01). Total encounter time fell an average of 121 seconds (95% CI 69 - 157 seconds, p\u3c0.001) in encounters that used the dashboard combined with the EHR. CONCLUSIONS: The integration of a hypertension-specific visual analytics dashboard with EHR demonstrates the potential to reduce time and improve hypertension guideline implementation. Further widespread testing in clinical practice is warranted

COVID-19 Vaccine Hesitancy among Arab Americans

Background: Coronavirus disease-2019 (COVID-19) vaccines have a significant impact on reducing morbidity and mortality from infection. However, vaccine hesitancy remains an obstacle in combating the pandemic. The Arab American (AA) population is understudied; thus, we aimed to explore COVID-19 attitudes within this community. Methods: This was a cross-sectional study. An anonymous online survey was distributed to members of different AA associations and to the community through the snowball method. Results: A total of 1746 participants completed the survey. A total of 92% of respondents reported having received at least one dose of a COVID-19 vaccine. A total of 73% reported willingness to receive a booster, and 72% plan to give their children the vaccine. On multivariate analysis, respondents were more likely to be vaccine-hesitant if they were hesitant about receiving any vaccine in general. They were less likely to be vaccine-hesitant if they were immigrants, over the age of 40, up to date on their general vaccination and if they believed that COVID-19 vaccines are safe and effective in preventing an infection. The belief that all vaccines are effective at preventing diseases was also associated with lower hesitancy. Conclusions: This sample of AAs have higher vaccination rates and are more willing to vaccinate their children against COVID-19 when compared to the rest of the population. However, a reemergence of hesitancy might be arising towards the boosters

A blood RNA transcriptome signature for COVID-19.

BACKGROUND: COVID-19 is a respiratory viral infection with unique features including a more chronic course and systemic disease manifestations including multiple organ involvement; and there are differences in disease severity between ethnic groups. The immunological basis for disease has not been fully characterised. Analysis of whole-blood RNA expression may provide valuable information on disease pathogenesis. METHODS: We studied 45 patients with confirmed COVID-19 infection within 10 days from onset of illness and a control group of 19 asymptomatic healthy volunteers with no known exposure to COVID-19 in the previous 14 days. Relevant demographic and clinical information was collected and a blood sample was drawn from all participants for whole-blood RNA sequencing. We evaluated differentially-expressed genes in COVID-19 patients (log2 fold change ≥ 1 versus healthy controls; false-discovery rate  0.05). CONCLUSIONS: The whole-blood transcriptome of COVID-19 has overall similarity with other respiratory infections but there are some unique pathways that merit further exploration to determine clinical relevance. The approach to a disease score may be of value, but needs further validation in a population with a greater range of disease severity