bioRxiv - Scientific Communication and Education最新文献

{"title":"Enhancing Light-Sheet Fluorescence Microscopy Illumination Beams through Deep Design Optimization","authors":"Chen Li, Mani R Rai, Yuheng Cai, H. Troy Ghashghaei, Alon Greenbaum","doi":"10.1101/2023.11.29.569329","DOIUrl":"https://doi.org/10.1101/2023.11.29.569329","url":null,"abstract":"Light sheet fluorescence microscopy (LSFM) provides the benefit of optical sectioning coupled with rapid acquisition times for imaging of tissue-cleared specimen. This allows for high-resolution 3D imaging of large tissue volumes. Inherently to LSFM, the quality of the imaging heavily relies on the characteristics of the illumination beam, with the notion that the illumination beam only illuminates a thin section that is being imaged. Therefore, substantial efforts are dedicated to identifying slender, non-diffracting beam profiles that can yield uniform and high-contrast images. An ongoing debate concerns the employment of the most optimal illumination beam; Gaussian, Bessel, Airy patterns and/or others. Comparisons among different beam profiles is challenging as their optimization objective is often different. Given that our large imaging datasets (~0.5TB images per sample) is already analyzed using deep learning models, we envisioned a different approach to this problem by hypothesizing that we can tailor the illumination beam to boost the deep learning models performance. We achieve this by integrating the physical LSFM illumination model after passing through a variable phase mask into the training of a cell detection network. Here we report that the joint optimization continuously updates the phase mask, improving the image quality for better cell detection. Our method's efficacy is demonstrated through both simulations and experiments, revealing substantial enhancements in imaging quality compared to traditional Gaussian light sheet. We offer valuable insights for designing microscopy systems through a computational approach that exhibits significant potential for advancing optics design that relies on deep learning models for analysis of imaging datasets.","PeriodicalId":501568,"journal":{"name":"bioRxiv - Scientific Communication and Education","volume":"54 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High Impact: Wikipedia sources and edit history document two decades of the climate change field","authors":"Omer Benjakob, Louise Jouveshomme, Matthieu Collet, Ariane Augustoni, Rona Aviram","doi":"10.1101/2023.11.30.569362","DOIUrl":"https://doi.org/10.1101/2023.11.30.569362","url":null,"abstract":"Since being founded in 2001, Wikipedia has grown into a trusted source of knowledge online, feeding Google search results and serving as training data for ChatGPT. Understanding the accuracy of its information, the sources behind its articles and their role in the transference of knowledge to the public are becoming increasingly important questions. Meanwhile, climate change has moved to the forefront of scientific and public discourse after years of warnings from the scientific community. Therefore, to understand how it was represented on English Wikipedia, we deployed a mixed-method approach on the article for \"Effects of climate change\" (ECC), its edit history and references, as well as hundreds of associated articles dealing with climate change in different ways. Using automated tools to scrape data from Wikipedia, we saw new articles were created as climatology-related knowledge grew and permeated into other fields, reflecting a growing body of climate research and growing public interest. Our qualitative textual analysis shows how specific descriptions of climatic phenomena became less hypothetical, reflecting the real-world public debate. The Intergovernmental Panel on Climate Change (IPCC) had a big impact on content and structure, we found using a bibliometric analysis, and what made this possible, we also discovered through a historical analysis, was the impactful work of just a few editors. This research suggests Wikipedia's articles documented the real-world events around climate change and its wider acceptance - initially a hypothesis that soon became a regretful reality. Overall, our findings highlight the unique role IPCC reports play in making scientific knowledge about climate change actionable to the public, and underscore Wikipedia's ability to facilitate access to research. This work demonstrates Wikipedia can be researched using both computational and qualitative methods to better understand transference of scientific information to the public and the history of contemporary science.","PeriodicalId":501568,"journal":{"name":"bioRxiv - Scientific Communication and Education","volume":"40 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Locally low-rank denoising in transform domains","authors":"Steen Moeller, Erick O Buko, Suhail Parvaze Pathan, Logan Dowdle, Kamil Ugurbil, Casey Johnson, Mehmet Akcakaya","doi":"10.1101/2023.11.21.568193","DOIUrl":"https://doi.org/10.1101/2023.11.21.568193","url":null,"abstract":"Purpose: To develop an extension to locally low rank (LLR) denoising techniques based on transform domain processing that reduces the number of images required in the MR image series for high-quality denoising.\u0000Theory and Methods: LLR methods with random matrix theory-based thresholds are successfully used in the denoising of MR image series in a number of applications. The performance of these methods depend on how well the LLR assumption is satisfied, which deteriorates with few numbers of images, as is commonly encountered in quantitative MRI applications. We propose a transform-domain approach for denoising of MR image series to represent the underlying signal with higher fidelity when using a locally low rank approximation. The efficacy of the method is demonstrated for fully-sampled k-space, undersampled k-space, DICOM images, and complex-valued SENSE-1 images in quantitative MRI applications with as few as 4 images.\u0000Results: For both MSK and brain applications, the transform domain denoising preserves local subtle variability, whereas the quantitative maps based on image domain LLR methods tend to be locally more homogeneous.\u0000Conclusion: A transform domain extension to LLR denoising produces high quality images and is compatible with both raw k-space data and vendor reconstructed data. This allows for improved imaging and more accurate quantitative analyses and parameters obtained therefrom.","PeriodicalId":501568,"journal":{"name":"bioRxiv - Scientific Communication and Education","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and Outcomes of an International Certificate Program in Science Policy and Advocacy for STEM PhD Students and Postdocs","authors":"Adriana Bankston, Amy Ralston, Joanne Ly, Harinder Singh","doi":"10.1101/2023.11.26.568726","DOIUrl":"https://doi.org/10.1101/2023.11.26.568726","url":null,"abstract":"Scientists must play a significant role in enacting societal change by educating and advising policymakers on relevant policy topics. To fill the identified gap in science policy and advocacy training, during the pandemic years, we piloted and offered the online Science Policy & Advocacy for STEM Scientists Certificate Program starting in 2020. Over three cohorts, the program was focused on practical skills and concepts, networking, and career development opportunities, and providing pathways for PhD students and postdoctoral researchers to learn about and in many cases fully transition into science policy and advocacy roles and careers. Program participants were exposed to many important aspects of what it means to be involved in science policy and advocacy, and many chose to enter the field through subsequent opportunities facilitated by the program training. We sought to reduce a number of barriers to program participation, and additionally provided resources for others to develop similar programs at their university. We believe this training model is innovative and can be recapitulated, and sincerely hope to see more universities create similar programs in the US and internationally in order to serve trainees interested in science policy and advocacy and facilitate their building impactful careers in the field for years to come.","PeriodicalId":501568,"journal":{"name":"bioRxiv - Scientific Communication and Education","volume":"90 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolving patterns of extremely productive publishing behavior across science","authors":"John Ioannidis, Thomas A Collins, Jeroen Baas","doi":"10.1101/2023.11.23.568476","DOIUrl":"https://doi.org/10.1101/2023.11.23.568476","url":null,"abstract":"We aimed to evaluate how many authors are extremely productive and how their presence across countries and scientific fields has changed during 2000-2022. Extremely productive (EP) authors were defined as those with >60 full papers (articles, reviews, conference papers) published in a single calendar year and indexed in Scopus. We identified 3,191 EP authors across science excluding Physics and 12,624 EP authors in Physics. While Physics had much higher numbers of EP authors in the past, in 2022 the number of EP authors was almost similar in non-Physics and Physics disciplines (1,226 vs. 1,480). Excluding Physics, China had the largest number of EP authors, followed by the USA. However, the largest fold-wise increases between 2016 and 2022 were seen in Thailand (19-fold), Saudi Arabia (11.5-fold), Spain (11.5-fold), India (10.2-fold), Italy (6.9-fold), Russia (6.5-fold), Pakistan (5.7-fold), and South Korea (5.2-fold). Excluding Physics, most EP authors were in Clinical Medicine, but from 2016 to 2022 the largest relative increases were seen in Agriculture, Fisheries & Forestry (14.6-fold), Biology (13-fold), and Mathematics and Statistics (6.1-fold). EP authors accounted for 4,360 of the 10,000 most-cited authors (based on raw citation count) across science. While most EP Physics authors had modest citation impact in a composite citation indicator that adjusts for co-authorship and author positions, 67% of EP authors in non-Physics fields remained within the top-2% according to that indicator among all authors with >=5 full papers. Extreme productivity has become worryingly common across scientific fields with rapidly increasing rates in some countries and settings.","PeriodicalId":501568,"journal":{"name":"bioRxiv - Scientific Communication and Education","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Promoting Transparent, Fair, and Inclusive Practices in Grantmaking: Lessons from the Open and Equitable Model Funding Program.","authors":"Eunice Mercado-Lara, Greg Tananbaum, Erin C McKiernan","doi":"10.1101/2023.11.15.567266","DOIUrl":"https://doi.org/10.1101/2023.11.15.567266","url":null,"abstract":"The Open Research Funders Group (ORFG) has been instrumental in promoting open and equitable scholarship to enhance academic\u0000research's transparency and accessibility. In 2020, the ORFG formed the Equity & Open Science Working Group, leading to the launch of the Open & Equitable Model Funding Program in 2021. This program aimed to refine grantmaking processes for broader inclusivity and equitable open scholarship practices.\u0000The program gathered a cohort of 11 funding organizations and focused on applying various proposed interventions within existing funding programs to improve grantmaking practices. The initiative highlighted the importance of targeted intervention selection and the need for delimited goal-setting, revealing challenges in implementation due to limited resources and the complexity of the processes involved.\u0000Participants valued the pilot for its structured approach and opportunities for shared learning despite some facing complexities in fully implementing the interventions. The ORFG's future approach involves flexible intervention selection, effective resource management, and fostering a collaborative community, aiming for a more inclusive and practical application of open scholarship principles.","PeriodicalId":501568,"journal":{"name":"bioRxiv - Scientific Communication and Education","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unveiling the Emotional Turmoil: How Covid-19 impacted researchers and the pursuit of emotional well-being in academia.","authors":"Crista Weise, Nuria Sole-Suner, Mariona Corcelles, Anna Sala-Bubare, Montserrat Castello","doi":"10.1101/2023.11.15.567306","DOIUrl":"https://doi.org/10.1101/2023.11.15.567306","url":null,"abstract":"The Covid-19 crisis unprecedentedly required researchers to adapt to significant changes in their work and personal lives. Our study aims to fill this gap analysing the Covid-19 emotional impact and confinement potential disruptions on researchers activity (specifically, those related to working conditions, caring responsibilities, health, balance, and social support) considering the modulating role played by age, gender, and job position. An online survey was distributed during the first lockdown period of the Covid-19 pandemic, and answers from 1301 researchers (ECR %, senior researchers %) working in Sciences (28.1%), Social Sciences (25.9%), Humanities (16.2%), Health (16.2%) and in Engineering and Architecture (13.5%) were collected. The study highlights that the initial lockdown during the Covid-19 pandemic had a significant emotional impact on researchers, exacerbating pre-existing emotional distress and burnout within this group. Factors such as age, health, gender, and difficulties in balancing work and family life were associated with an increased risk of burnout and emotional distress. Lack of social support was identified as a significant risk factor, while the academic culture prioritizing productivity over well-being contributed to the issue. These findings underscore the need for greater support and cultural changes in academia to preserve researchers' mental health and prevent the chronicization of mental health issues in young academics.","PeriodicalId":501568,"journal":{"name":"bioRxiv - Scientific Communication and Education","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138544311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}