COVID-19 update: the first 6 months of the pandemic

The COVID-19 pandemic is sweeping the world and will feature prominently in all our lives for months and most likely for years to come. We review here the current state 6 months into the declared pandemic. Specifically, we examine the role of the pathogen, the host and the environment along with the possible role of diabetes. We also firmly believe that the pandemic has shown an extraordinary light on national and international politicians whom we should hold to account as performance has been uneven. We also call explicitly on competent leadership of international organizations, specifically the WHO, UN and EU, informed by science. Finally, we also condense successful strategies for dealing with the current COVID-19 pandemic in democratic countries into a developing pandemic playbook and chart a way forward into the future. This is useful in the current COVID-19 pandemic and, we hope, in a very distant future again when another pandemic might arise

Alzheimer's disease: using gene/protein network machine learning for molecule discovery in olive oil

Alzheimer's disease (AD) poses a profound human, social, and economic burden. Previous studies suggest that extra virgin olive oil (EVOO) may be helpful in preventing cognitive decline. Here, we present a network machine learning method for identifying bioactive phytochemicals in EVOO with the highest potential to impact the protein network linked to the development and progression of the AD. A balanced classification accuracy of 70.3 ± 2.6% was achieved in fivefold cross-validation settings for predicting late-stage experimental drugs targeting AD from other clinically approved drugs. The calibrated machine learning algorithm was then used to predict the likelihood of existing drugs and known EVOO phytochemicals to be similar in action to the drugs impacting AD protein networks. These analyses identified the following ten EVOO phytochemicals with the highest likelihood of being active against AD: quercetin, genistein, luteolin, palmitoleate, stearic acid, apigenin, epicatechin, kaempferol, squalene, and daidzein (in the order from the highest to the lowest likelihood). This in silico study presents a framework that brings together artificial intelligence, analytical chemistry, and omics studies to identify unique therapeutic agents. It provides new insights into how EVOO constituents may help treat or prevent AD and potentially provide a basis for consideration in future clinical studies

Bottom-up visions for future of food growing in cities

We report on community food growing as an instance of practice-based sustainability research focused on the design of interactive systems for food growing in future cities. We present a case study with a series of workshops using speculative and participatory design approaches focused on creatively exploring futures of urban food growing with a local neighbourhood community. Working with local grassroots communities is often perceived as more egalitarian for promoting viable long-term and embedded change in cities, yet little work has studied this approach for urban food growing. To explore how we might better articulate and conceptualize collaborative food growing futures, we discuss the creation of bottom-up visions as contestations to hegemonic narratives of power and control in cities. These are affected by, limitations of present resources and infrastructures, inability to work at scale due to lack of buy-in of stakeholders, and erroneous promises of future technologies. Through these reflections on grassroots futures as complex assemblages of social and material realities, we provoke researchers and practitioners to look at envisioning future possibilities with participants, as a web of practices and stakeholders. We further suggest that researchers and practitioners explore these interconnections through assemblages of socio-material realities and visions of high- and low-tech futures. This work is important because it provides a new approach to looking at the design of future technologies for cities and addressing systemic issues of hegemonic food systems through bottom-up actionable futures

Randomized controlled trial of a group peer mentoring model for U.S. academic medicine research faculty

Abstract Introduction:Midcareer is a critical transition point for biomedical research faculty and a common dropout point from an NIH-funded career. We report a study to assess the efficacy of a group peer mentoring program for diverse biomedical researchers in academic medicine, seeking to improve vitality, career advancement, and cross-cultural competence. Methods:We conducted a stratified randomized controlled trial with a waitlist control group involving 40 purposefully diverse early midcareer research faculty from 16 states who had a first-time NIH R01 (or equivalent) award, a K training grant, or a similar major grant. The yearlong intervention (2 to 3 days quarterly) consisted of facilitated, structured, group peer mentoring. Main study aims were to enhance faculty vitality, self-efficacy in achieving research success, career advancement, mentoring others, and cultural awareness and appreciation of diversity in the workplace. Results:Compared to the control group, the intervention group’s increased vitality did not reach statistical significance (P = 0.20), but perceived change in vitality was 1.47 standard deviations higher (D = 1.47, P = 0.03). Self-efficacy for career advancement was higher in the intervention group (D = 0.41, P = 0.05) as was self-efficacy for research (D = 0.57, P = 0.02). The intervention group also valued diversity higher (D = 0.46, P = 0.02), had higher cognitive empathy (D = 0.85, P = 0.03), higher anti-sexism/racism skills (D = 0.71, P = 0.01), and higher self-efficacy in mentoring others (D = 1.14, P = 0.007). Conclusions:The mentoring intervention resulted in meaningful change in important dimensions and skills among a national sample of diverse early midcareer biomedical faculty. This mentoring program holds promise for addressing the urgencies of sustaining faculty vitality and cross-cultural competence

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources

Revised nomenclature for the mammalian long-chain acyl-CoA synthetase gene family.

By consensus, the acyl-CoA synthetase (ACS) community, with the advice of the human and mouse genome nomenclature committees, has revised the nomenclature for the mammalian long-chain acyl-CoA synthetases. ACS is the family root name, and the human and mouse genes for the long-chain ACSs are termed ACSL1,3-6 and Acsl1,3-6, respectively. Splice variants of ACSL3, -4, -5, and -6 are cataloged. Suggestions for naming other family members and for the nonmammalian acyl-CoA synthetases are made

International study on nurses' views and experiences of compassion

BACKGROUND: Compassion is considered the cornerstone of nursing practice. However, the recent failures in delivering high-quality compassionate nursing care in the UK's National Health Service have brought the topic of compassion to the attention of the public, service providers, policy makers and academics. AIM: The aim of this study was to explore the nurses' views and experiences of a number of compassion-related issues in nursing and describe similarities and differences at an international level as well as from the different nursing roles of the participating nurses. METHODS: An exploratory, cross-sectional descriptive study, using the International Online Compassion Questionnaire. A total of 1323 nurses from 15 countries completed the questionnaire. RESULTS: The majority of participants (59.5%) defined compassion as "Deep awareness of the suffering of others and wish to alleviate it" but definitions of compassion varied by country. Of participants, 69.6% thought compassion was very important in nursing and more than half (59.6%) of them argued that compassion could be taught. However, only 26.8% reported that the correct amount and level of teaching is provided. The majority of the participants (82.6%) stated that their patients prefer knowledgeable nurses with good interpersonal skills. Only 4.3% noted that they are receiving compassion from their managers. A significant relationship was found between nurses' experiences of compassion and their views about teaching of compassion. CONCLUSION: Our study is unique in identifying the views and experiences of nurses from 15 different countries worldwide. The findings reveal that compassion is neither addressed adequately in nursing education nor supported in the practice environment by managers. LIMITATIONS: Self-report bias was inherent to our survey study design. Furthermore, the individual cultural differences and similarities in the findings are difficult to extrapolate owing to the fact that our analysis was at country level, as well as at the level of the participating nurses. IMPLICATIONS FOR NURSING POLICY: Understanding the influence of culture on nurses' views about compassion is critical in the current multicultural healthcare environment and merits further research. This will potentially drive changes in nursing education (ensuring that compassion is taught to nurses) and in the way healthcare leaders and managers foster a compassionate culture within their organizations (e.g. by leading by example and compassionate to their staff). © 2016 International Council of Nurses

Strange homelands: encountering the migrant on the contemporary Greek stage

This article examines three examples from recent Greek theatre which stage experiences of migrants and refugees against the backdrop of Greece’s growing internationalism and multiculturalism. In allowing migrants to author their own narratives of border-crossing and encountering their new “homeland”, those theatrical endeavours, I argue, attempt to break the monologism of Greek theatre and monolithic understandings of national identity thus opening up spaces for encountering diverse voices. In acknowledging the risks and tensions underpinning the migrant’s presence on stage, the article also applies pressure to questions of encounter, authenticity, representation and self-expression of migratory subjects and interrogates some ways in which they navigate their precarious space of belonging and author themselves in the context of contemporary Greek theatre