A tool that could suggest new personalized research directions and ideas by taking insights from the scientific literature could profoundly accelerate the progress of science. A field that might benefit from such an approach is artificial intelligence (AI) research, where the number of scientific publications has been growing exponentially over recent years, making it challenging for human researchers to keep track of the progress. Here we use AI techniques to predict the future research directions of AI itself. We introduce a graph-based benchmark based on real-world data—the Science4Cast benchmark, which aims to predict the future state of an evolving semantic network of AI. For that, we use more than 143,000 research papers and build up a knowledge network with more than 64,000 concept nodes. We then present ten diverse methods to tackle this task, ranging from pure statistical to pure learning methods. Surprisingly, the most powerful methods use a carefully curated set of network features, rather than an end-to-end AI approach. These results indicate a great potential that can be unleashed for purely ML approaches without human knowledge. Ultimately, better predictions of new future research directions will be a crucial component of more advanced research suggestion tools.

AbstractThe longevity field has received an influx of capital and talent over the past 5 years, but it is unclear where directing these resources would result in the biggest positive impact. We aimed to establish a systematic, rigorous and unbiased way to identify the areas where increased investment would accelerate progress across the whole longevity field the most. To do so, we surveyed ∼400 participants across various sectors of longevity, asking them to 1) identify the major bottlenecks they are experiencing, 2) list their most needed solution, and 3) rate the potential efficacy and barriers to development of various aging intervention strategies. We built a classification system of Bottlenecks and Solutions based on grouping related answers and found the most frequently listed bottlenecks to be 1) lack of validated aging biomarkers; 2) an overall lack of funding; and 3) lack of good models for aging studies. Surprisingly, the most wanted solution was greater availability of large public datasets. Indeed, a common theme across all answers was the need for a new data-centric structure of scientific research, where large datasets are routinely gathered and made available, access walls are removed, protocols are standardized, negative and unpublished data are shared, and AI systems are released on the data for automated discovery. Finally, a lack of regulatory clarity was listed as the biggest barrier to development across all interventions, whereas cellular reprogramming, organ replacement, and genetic medicine (gene therapies and gene editing) were perceived as the intervention strategies with the highest potential for increasing healthy lifespan. We provide these data as a resource for funding agencies, philanthropists, entrepreneurs and newcomers to the field as a means to identify high impact areas to fund and work on.Key takeaways395 Participants were surveyed for their biggest bottlenecks and most needed solutionsTop Bottlenecks: lack of Validated Biomarkers; Overall lack of Funding and Slow & Expensive Models.Top proposed Solutions: more Public Datasets; improved Regulatory Path; and Overall More Funding.Bottlenecks and Solutions vary substantially across industry areas.Rapamycin and calorie restriction are perceived as the most efficacious interventions in the near term.Somatic reprogramming, organ replacement, and genetic medicine are perceived as the most efficacious interventions in the long term (25 years).Sirtuin and NAD targeting therapies are seen as the least efficacious interventions in all time-frames.Across all interventions, Regulatory Issues are perceived as the most severely inhibiting factor in the development of the intervention.

Eelgrass cover extent is among the most reliable indicators for measuring changes in coastal ecosystems. Eelgrass has colonized the mouth of the Romaine River and has become a part of environmental monitoring there since 2013. The presence of eelgrass in this area is an essential factor for the early detection of changes in the Romaine coastal ecosystem. This will act as a trigger for an appropriate environmental response to preserve ecosystem health. In this paper, a cost- and time-efficient workflow for such spatial monitoring is proposed using a pixel-oriented k-NN algorithm. It can then be applied to multiple modellers to efficiently map the eelgrass cover. Training data were collected to define key variables for segmentation and k-NN classification, providing greater edge detection for the presence of eelgrass. The study highlights that remote sensing and training data must be acquired under similar conditions, replicating methodologies for collecting data on the ground. Similar approaches must be used for the zonal statistic requirements of the monitoring area. This will allow a more accurate and reliable assessment of eelgrass beds over time. An overall accuracy of over 90% was achieved for eelgrass detection for each year of monitoring.

BackgroundThe migration of healthcare workers (HWs) from low/middle-income countries (LMICs) is a pressing global health issue with implications for population-level health outcomes. We aimed to synthesise the drivers of HWs’ out-migration, intention to migrate and non-migration from LMICs.MethodsWe searched Ovid MEDLINE, EMBASE, CINAHL, Global Health and Web of Science, as well as the reference lists of retrieved articles. We included studies (quantitative, qualitative or mixed-methods) on HWs’ migration or intention to migrate, published in either English or French between 1 January 1970 and 31 August 2022. The retrieved titles were deduplicated in EndNote before being exported to Rayyan for independent screening by three reviewers.ResultsWe screened 21 593 unique records and included 107 studies. Of the included studies, 82 were single-country studies focusing on 26 countries, while the remaining 25 included data from multiple LMICs. Most of the articles focused on either doctors 64.5% (69 of 107) and/or nurses 54.2% (58 of 107). The UK (44.9% (48 of 107)) and the USA (42% (45 of 107)) were the top destination countries. The LMICs with the highest number of studies were South Africa (15.9% (17 of 107)), India (12.1% (13 of 107)) and the Philippines (6.5% (7 of 107)). The major drivers of migration were macro-level and meso-level factors. Remuneration (83.2%) and security problems (58.9%) were the key macro-level factors driving HWs’ migration/intention to migrate. In comparison, career prospects (81.3%), good working environment (63.6%) and job satisfaction (57.9%) were the major meso-level drivers. These key drivers have remained relatively constant over the last five decades and did not differ among HWs who have migrated and those with intention to migrate or across geographical regions.ConclusionGrowing evidence suggests that the key drivers of HWs’ migration or intention to migrate are similar across geographical regions in LMICs. Opportunities exist to build collaborations to develop and implement strategies to halt this pressing global health problem.

Early successes in controlling the COVID-19 pandemic have prevented Republic of Korea from implementing a prompt, large-scale vaccine rollout to the public. The influence of traditional media on public opinion remains critical and substantial in Republic of Korea, and there have been heated debates about vaccination in traditional media reports in Korea. Effective and efficient public health communication is integral in managing public health challenges. This study explored media reports on the COVID-19 vaccines during the pandemic in Republic of Korea. 12,399 media news reports from May 2020 to September 2021 were collected. An LDA topic model was applied in order to analyze and compare the topics drawn from each study phase using words from the unstructured text data. Although media reports from before the national vaccination implementation focused on the development and rollout of COVID-19 vaccines, diverse topics were reported without any overlap. After the vaccination rollout, the biggest concern was the side effects of the COVID-19 vaccine. In sum, Republic of Korea's major media outlets reported on diverse topics rather than generating a common discourse about topics related to COVID-19 vaccination.

IntroductionThe WHO estimates a shortage of 18 million health workers (HWs) by 2030, primarily in low-income and middle-income countries (LMICs). The perennial out-migration of HWs from LMICs, often to higher-income countries, further exacerbates the shortage. We propose a systematic review to understand the determinants of HWs out-migration, intention to migrate and non-migration from LMICs.Methods and analysisThis protocol was designed in accordance with the Preferred Reporting Items for Systematic Review and Meta-analysis Protocols guideline for the development and reporting of systematic review protocols. We will include English and French language primary studies (quantitative or qualitative) focused on any category of HWs; from any LMICs; assessed migration or intention to migrate; and reported any determinant of migration. A three-step search strategy that involves a search of one electronic database to refine the preliminary strategy, a full search of all included databases and reference list search of included full-text papers for additional articles will be employed. We will search Ovid MEDLINE, EMBASE, CINAHL, Global Health and Web of Science from inception to August 2022. The retrieved titles will be imported to EndNote and deduplicated. Two reviewers will independently screen all titles and abstract for eligibility using Rayyan. Risk of bias of the individual studies will be determined using the National Institute of Health study quality assessment tools for quantitative studies and the 10-item Critical Appraisal Skills Programme checklists for qualitative studies. The results will be presented in the form of narrative synthesis using a descriptive approachEthics and disseminationWe will not seek ethical approval from an institutional review board, as this is a systematic review. At completion, we will submit the report of this review to a peer-reviewed journal for publication. Key findings will be presented at local and international conferences.PROSPERO registration numberCRD42022334283.

AbstractBackgroundAcetylcholinesterase inhibitors (AChEIs) enhance cognitive functioning in Alzheimer’s disease (AD). The use of AChEIs at therapeutic doses is limited by gastrointestinal (GI) side effects, such as nausea, vomiting and diarrhea. Alpha‐1062 is a pharmacologically inactive prodrug of the AChEI galantamine specifically designed to reduce or eliminate GI side effects and provide increased safety. In addition to its activity as an AChEI, galantamine exhibits a second important mechanism of action, binding allosterically to nicotinic cholinergic receptors enhancing their responsiveness to acetylcholine. In Phase 1 single ascending dose (SAD) and multiple ascending dose (MAD) trials in young and elderly healthy subjects, Alpha‐1062 demonstrated both evidence of an improved GI side effect profile and enhanced cognition. Here we extend the findings of the SAD and MAD studies with an additional analysis of the effects of Alpha‐1062 on quantitative‐EEG (qEEG) data collected as part of the MAD study.MethodsSubjects (n = 12/dose) were administered two doses per day of Alpha‐1062 for 7 consecutive days. Pharmaco‐EEG measurements were performed for 4 min eyes closed / 4 min eyes open, on day 1 and day 7 at various timepoints both pre‐dose and post‐dose using a standard 10‐20 electrode montage with 21 channels. qEEG data analysis was conducted using qEEG indices developed using a machine learning algorithm based on the analysis of 39 AD patients administered galantamine (Sci Rep 7, 5775 [2017]). These were an AD index and a galantamine index, which were expected to be sensitive to the effects of Alpha 1062 administration.ResultsIn healthy elderly subjects, Alpha‐1062 administration improved response on the AD index (p <0.05) compared to placebo, at the pre‐dose timepoint on day 7. The AD index was also reduced at all post‐dose timepoints on day 7 relative to placebo. Changes in several other relevant measures of qEEG function suggested Alpha‐1062 improved brain function.ConclusionThese data demonstrate the potential benefit Alpha‐1062 in the treatment of AD. Alpha‐1062 was safe in the dose range investigated, and influenced pharmaco‐EEG outcomes in healthy elderly subjects that were consistent with the previously documented positive effects in tests related to sustained attention and working memory.