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Understanding “how to optimize the production of scientific knowledge” is paramount to those who support scientific research—funders as well as research institutions—to the communities served, and to researchers. Structured archives can help all involved to learn what decisions and processes help or hinder the production of new knowledge. Using artificial intelligence (AI) and large language models (LLMs), we recently created the first structured digital representation of the historic archives of the National Human Genome Research Institute (NHGRI), part of the National Institutes of Health. This work yielded a digital knowledge base of entities, topics, and documents that can be used to probe the inner workings of the Human Genome Project, a massive international public-private effort to sequence the human genome, and several of its offshoots like The Cancer Genome Atlas (TCGA) and the Encyclopedia of DNA Elements (ENCODE). The resulting knowledge base will be instrumental in understanding not only how the Human Genome Project and genomics research developed collaboratively, but also how scientific goals come to be formulated and evolve. Given the diverse and rich data used in this project, we evaluated the ethical implications of employing AI and LLMs to process and analyze this valuable archive. As the first computational investigation of the internal archives of a massive collaborative project with multiple funders and institutions, this study will inform future efforts to conduct similar investigations while also considering and minimizing ethical challenges. Our methodology and risk-mitigating measures could also inform future initiatives in developing standards for project planning, policymaking, enhancing transparency, and ensuring ethical utilization of artificial intelligence technologies and large language models in archive exploration.Author Contributions: Mohammad Hosseini: Investigation; Project Administration; Writing – original draft; Writing – review & editing. Spencer Hong: Conceptualization, Data curation, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing. Thomas Stoeger: Conceptualization; Investigation; Project Administration; Supervision; Writing – original draft; Writing – review & editing. Kristi Holmes: Funding acquisition, Supervision, Writing – review & editing. Luis A. Nunes Amaral: Funding acquisition, Supervision, Writing – review & editing. Christopher Donohue: Conceptualization, Project administration, Resources, Supervision, Writing – original draft, Writing – review & editing. Kris Wetterstrand: Conceptualization, Funding acquisition, Project administration. 

Abstract The Midwest Aging Consortium (MAC) has emerged as a critical collaborative initiative aimed at advancing our understanding of aging and developing strategies to combat the rising prevalence of age-related diseases. Founded in 2019, MAC brings together researchers from various disciplines and institutions across the Midwestern United States to foster interdisciplinary geroscience research. This report summarizes the highlights of the Fourth Annual Symposium of MAC, which was held at Iowa State University in May 2023. The symposium featured presentations on a wide array of topics, including studies on slow-aging animals, cellular senescence and senotherapeutics, the role of the immune system in aging, metabolic changes in aging, neuronal health in aging, and biomarkers for measuring the aging process. Speakers shared findings from studies involving a variety of animals, ranging from commonly used species such as mice, rats, worms, yeast, and fruit flies, to less-common ones like naked mole-rats, painted turtles, and rotifers. MAC continues to emphasize the importance of supporting emerging researchers and fostering a collaborative environment, positioning itself as a leader in aging research. This symposium not only showcased the current state of aging biology research but also highlighted the consortium’s role in training the next generation of scientists dedicated to improving the healthspan and well-being of the aging population. 

Abstract Human gene research generates new biology insights with translational potential, yet few studies have considered the health of the human gene literature. The accessibility of human genes for targeted research, combined with unreasonable publication pressures and recent developments in scholarly publishing, may have created a market for low-quality or fraudulent human gene research articles, including articles produced by contract cheating organizations known as paper mills. This review summarises the evidence that paper mills contribute to the human gene research literature at scale and outlines why targeted gene research may be particularly vulnerable to systematic research fraud. To raise awareness of targeted gene research from paper mills, we highlight features of problematic manuscripts and publications that can be detected by gene researchers and/or journal staff. As improved awareness and detection could drive the further evolution of paper mill-supported publications, we also propose changes to academic publishing to more effectively deter and correct problematic publications at scale. In summary, the threat of paper mill-supported gene research highlights the need for all researchers to approach the literature with a more critical mindset, and demand publications that are underpinned by plausible research justifications, rigorous experiments and fully transparent reporting. 

Throughout the last 2 decades, several scholars observed that present day research into human genes rarely turns toward genes that had not already been extensively investigated in the past. Guided by hypotheses derived from studies of science and innovation, we present here a literature-wide data-driven meta-analysis to identify the specific scientific and organizational contexts that coincided with early-stage research into human genes throughout the past half century. We demonstrate that early-stage research into human genes differs in team size, citation impact, funding mechanisms, and publication outlet, but that generalized insights derived from studies of science and innovation only partially apply to early-stage research into human genes. Further, we demonstrate that, presently, genome biology accounts for most of the initial early-stage research, while subsequent early-stage research can engage other life sciences fields. We therefore anticipate that the specificity of our findings will enable scientists and policymakers to better promote early-stage research into human genes and increase overall innovation within the life sciences. 

Nucleotide sequence reagents underpin molecular techniques that have been applied across hundreds of thousands of publications. We have previously reported wrongly identified nucleotide sequence reagents in human research publications and described a semi-automated screening tool Seek & Blastn to fact-check their claimed status. We applied Seek & Blastn to screen >11,700 publications across five literature corpora, including all original publications in Gene from 2007 to 2018 and all original open-access publications in Oncology Reports from 2014 to 2018. After manually checking Seek & Blastn outputs for >3,400 human research articles, we identified 712 articles across 78 journals that described at least one wrongly identified nucleotide sequence. Verifying the claimed identities of >13,700 sequences highlighted 1,535 wrongly identified sequences, most of which were claimed targeting reagents for the analysis of 365 human protein-coding genes and 120 non-coding RNAs. The 712 problematic articles have received >17,000 citations, including citations by human clinical trials. Given our estimate that approximately one-quarter of problematic articles may misinform the future development of human therapies, urgent measures are required to address unreliable gene research articles. 

It is known that research into human genes is heavily skewed towards genes that have been widely studied for decades, including many genes that were being studied before the productive phase of the Human Genome Project. This means that the genes most frequently investigated by the research community tend to be only marginally more important to human physiology and disease than a random selection of genes. Based on an analysis of 10,395 research publications about SARS-CoV-2 that mention at least one human gene, we report here that the COVID-19 literature up to mid-October 2020 follows a similar pattern. This means that a large number of host genes that have been implicated in SARS-CoV-2 infection by four genome-wide studies remain unstudied. While quantifying the consequences of this neglect is not possible, they could be significant.