International research collaboration: The way forward
Bibliographic record
Abstract
Academic respiratory medicine is entering a new and exciting era; one where diagnostic challenges are emerging, newer multi-omic technologies are being increasingly applied and complex bioinformatic challenges involving artificial intelligence have arrived. The Singapore International Respiratory Consortium (SIRC) was formed in 2016 at a workshop convened at the National University of Singapore (NUS) to discuss and formalize collaborations that will address these challenges within the Asia-Pacific region and globally. The second International Symposium on Respiratory Research was convened at the Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Singapore in March 2018 and included leaders in Respiratory Research from NTU, NUS, the University of Newcastle, Australia (UON), Karolinska Institutet (KI), Imperial College London (ICL), the University of British Columbia (UBC) and the University of Groningen (RUG). The consortium focused on three major themes and coincided with the formal launch of The Academic Respiratory Initiative for Pulmonary Health (TARIPH), a Singapore-centric interdisciplinary respiratory research network.1 Respiratory disease causes an immense worldwide health burden. Current World Health Organization (WHO) estimates show that more than 1 billion people suffer from chronic respiratory conditions. This number continues to increase, causing significant disability and death. Teams must be ready to respond to such global health challenges in an ever-changing research environment. The SIRC was established as a vehicle to foster international collaborative research to address the global impact of respiratory disease. Within this framework, a key objective of the consortium is to inspire and mentor the next generation of outstanding researchers. The workshop was organized into three themes: (i) Respiratory Infection and the Microbiome; (ii) Bioengineering, Nanomedicine and other innovations; and (iii) Respiratory Physiology, Therapeutics and Service Impact. These areas, while seemingly diverse harnessed the strengths of participating institutions across a range of basic science, translational and clinical research that underpins respiratory health and disease. By necessity, a number of areas of investigation relevant to chronic respiratory disease, including aspects of clinical science, were not addressed in this symposium. However, with investigators from large Consortium-based studies such as U-BIOPRED and the Canadian Healthy Infant Longitudinal Development (CHILD) attending, opportunities to highlight knowledge gaps and provide recommendations for strategic planning and future research to better understand, prevent and treat chronic respiratory diseases were presented and discussed. Respiratory Infection and Microbiome: The increasing prevalence of respiratory infections highlights the urgent need to evaluate the impact of the inhaled environment on lung health and disease. Investigations of the lung microbiome, the lung-gut axis, fungi and their impact are rapidly developing but many require an in-depth understanding of bioinformatics to appreciate. Newer microbiomes, such as the air microbiome, are exciting and will no doubt add important pieces to the puzzle. While the complexity of these ‘ecosystems’ provides rich data sets, a complete systems biology approach will be necessary to unravel them. Bioengineering, Nanomedicine and other respiratory innovations: A translation of understanding disease mechanisms to the development of diagnostic biomarkers and therapeutic agents is enhanced by the improved in vitro, ex vivo and in vivo model systems and methodologies for analysing the data they produce. For example, using three-dimensional (3D) lung organoid cultures offers a more architecturally ‘relevant’ model for understanding cell–cell interactions, while a 3D extracellular matrix provides key insight into the cell–environment interaction. Developing novel approaches to delivering antibiotics or generating cell-specific nanoparticles that allow higher payload delivery to specific cell types within a complex tissue offers new hope towards a targeted pulmonary drug delivery platform. Respiratory Physiology, Therapeutics and Service Impact: While repurposing existing therapeutics or identifying targets involved in multiple pathways are novel, cost-effective approaches in treating respiratory disease, the precision medicine era necessitates a more integrated approach. This includes a mechanistic appreciation of the interplay between genetics, epigenetics and developmental pathways from lung development and repair through their impact on responses to medications, biomarkers, host immunity and lung function. Rapid point-of-care diagnostics will be a major component to precision medicine with the very real potential to substantially reduce health care spending. The themes underpinning this symposium were intended to foster international collaborative research addressing several fundamental challenges that underpin chronic respiratory disease and its treatment. Within this framework, a key objective was to inspire the next generation of outstanding researchers. The topics discussed in each theme created a strategic blueprint for transdisciplinary and networked research including academic and post-graduate student exchange to achieve these goals and ultimately to improve patient care and the global health burden of respiratory disease. In a recent ‘Letter from Singapore’, the need for a ‘national academic platform’ to bring academics, clinicians and other stakeholders together for a combined collaborative effort was proposed.1 In opening this year's meeting, this vision became reality.2 The TARIPH was launched and will focus on performing collaborative interdisciplinary research focused on respiratory health and disease. TARIPH aims to ‘bring research to patients through partnerships’ and encourages individuals, groups, academic institutions, clinical sites and industrial partners to work more closely together to improve lung health and address respiratory disease. By providing a strong combined research platform encompassing basic science, translational and clinical arms, it builds upon existing academic and clinical strengths whilst synergizing Singapore's national efforts in respiratory academia. The authors thank the following speakers and participants of the symposium; NTU: Sanjay Chotirmall, Helen Smith, Mary Bee Eng Chan, Stephan Schuster, Eric Yap; UON: Darryl Knight, Paul Foster, Phil Hansbro, Nathan Bartlett; NUS: W.S. Fred Wong, Thai Tran, LIM Hui Fang, Wang De Yun; UBC: Dermot Kelleher, Chris Carlsten, Janice Leung; ICL: K. Fan Chung, Ian Adcock, Darius Armstrong-James; KI: Sven Erik Dahlen, Craig Wheelock; RUG: Han Moshage, Reinoud Gosens, Janette Burgess.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".