Lu Wang, Li Chang, Ruipeng Zhang, Kexun Li, Yu Wang, Wei Chen, Xuanlin Feng, Mingwei Sun, Qi Wang, Charles Damien Lu, Jun Zeng, Hua Jiang
Background and Objectives: We aim to establish deep learning models to optimize the individualized energy delivery for septic patients. Methods and Study Design: We conducted a study of adult septic patients in Intensive Care Unit (ICU), collecting 47 indicators for 14 days. After data cleaning and preprocessing, we used stats to explore energy delivery in deceased and surviving patients. We filtered out nutrition-related features and divided the data into three metabolic phases: acute early, acute late, and rehabilitation. Models were built using data before September 2020 and validated on the rest. We then established optimal energy target models for each phase using deep learning. Results: A total of 277 patients and 3115 data were included in this study. The models indicated that the optimal energy targets in the three phases were 900kcal/d, 2300kcal/d, and 2000kcal/d, respectively. Excessive energy intake increased mortality rapidly in the early period of the acute phase. Insufficient energy in the late period of the acute phase significantly raised the mortality of septic patients. For the rehabilitation phase, too much or too little energy delivery both associated with high mortality. Conclusion: Our study established time-series prediction models for septic patients to optimize energy delivery in the ICU. This approach indicated the feasibility of developing nutritional tools for critically ill patients. We recommended permissive underfeeding only in the early acute phase. Later, increased energy intake may improve survival and settle energy debts caused by underfeeding.
{"title":"Optimize Individualized Energy Delivery for Septic Patients Using Predictive Deep Learning Models: A Real World Study","authors":"Lu Wang, Li Chang, Ruipeng Zhang, Kexun Li, Yu Wang, Wei Chen, Xuanlin Feng, Mingwei Sun, Qi Wang, Charles Damien Lu, Jun Zeng, Hua Jiang","doi":"arxiv-2402.02201","DOIUrl":"https://doi.org/arxiv-2402.02201","url":null,"abstract":"Background and Objectives: We aim to establish deep learning models to\u0000optimize the individualized energy delivery for septic patients. Methods and\u0000Study Design: We conducted a study of adult septic patients in Intensive Care\u0000Unit (ICU), collecting 47 indicators for 14 days. After data cleaning and\u0000preprocessing, we used stats to explore energy delivery in deceased and\u0000surviving patients. We filtered out nutrition-related features and divided the\u0000data into three metabolic phases: acute early, acute late, and rehabilitation.\u0000Models were built using data before September 2020 and validated on the rest.\u0000We then established optimal energy target models for each phase using deep\u0000learning. Results: A total of 277 patients and 3115 data were included in this\u0000study. The models indicated that the optimal energy targets in the three phases\u0000were 900kcal/d, 2300kcal/d, and 2000kcal/d, respectively. Excessive energy\u0000intake increased mortality rapidly in the early period of the acute phase.\u0000Insufficient energy in the late period of the acute phase significantly raised\u0000the mortality of septic patients. For the rehabilitation phase, too much or too\u0000little energy delivery both associated with high mortality. Conclusion: Our\u0000study established time-series prediction models for septic patients to optimize\u0000energy delivery in the ICU. This approach indicated the feasibility of\u0000developing nutritional tools for critically ill patients. We recommended\u0000permissive underfeeding only in the early acute phase. Later, increased energy\u0000intake may improve survival and settle energy debts caused by underfeeding.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"2017 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139771452","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}
AI-enabled synthetic biology has tremendous potential but also significantly increases biorisks and brings about a new set of dual use concerns. The picture is complicated given the vast innovations envisioned to emerge by combining emerging technologies, as AI-enabled synthetic biology potentially scales up bioengineering into industrial biomanufacturing. However, the literature review indicates that goals such as maintaining a reasonable scope for innovation, or more ambitiously to foster a huge bioeconomy don't necessarily contrast with biosafety, but need to go hand in hand. This paper presents a literature review of the issues and describes emerging frameworks for policy and practice that transverse the options of command-and control, stewardship, bottom-up, and laissez-faire governance. How to achieve early warning systems that enable prevention and mitigation of future AI-enabled biohazards from the lab, from deliberate misuse, or from the public realm, will constantly need to evolve, and adaptive, interactive approaches should emerge. Although biorisk is subject to an established governance regime, and scientists generally adhere to biosafety protocols, even experimental, but legitimate use by scientists could lead to unexpected developments. Recent advances in chatbots enabled by generative AI have revived fears that advanced biological insight can more easily get into the hands of malignant individuals or organizations. Given these sets of issues, society needs to rethink how AI-enabled synthetic biology should be governed. The suggested way to visualize the challenge at hand is whack-a-mole governance, although the emerging solutions are perhaps not so different either.
{"title":"The whack-a-mole governance challenge for AI-enabled synthetic biology: literature review and emerging frameworks","authors":"Trond Arne Undheim","doi":"arxiv-2402.00312","DOIUrl":"https://doi.org/arxiv-2402.00312","url":null,"abstract":"AI-enabled synthetic biology has tremendous potential but also significantly\u0000increases biorisks and brings about a new set of dual use concerns. The picture\u0000is complicated given the vast innovations envisioned to emerge by combining\u0000emerging technologies, as AI-enabled synthetic biology potentially scales up\u0000bioengineering into industrial biomanufacturing. However, the literature review\u0000indicates that goals such as maintaining a reasonable scope for innovation, or\u0000more ambitiously to foster a huge bioeconomy don't necessarily contrast with\u0000biosafety, but need to go hand in hand. This paper presents a literature review\u0000of the issues and describes emerging frameworks for policy and practice that\u0000transverse the options of command-and control, stewardship, bottom-up, and\u0000laissez-faire governance. How to achieve early warning systems that enable\u0000prevention and mitigation of future AI-enabled biohazards from the lab, from\u0000deliberate misuse, or from the public realm, will constantly need to evolve,\u0000and adaptive, interactive approaches should emerge. Although biorisk is subject\u0000to an established governance regime, and scientists generally adhere to\u0000biosafety protocols, even experimental, but legitimate use by scientists could\u0000lead to unexpected developments. Recent advances in chatbots enabled by\u0000generative AI have revived fears that advanced biological insight can more\u0000easily get into the hands of malignant individuals or organizations. Given\u0000these sets of issues, society needs to rethink how AI-enabled synthetic biology\u0000should be governed. The suggested way to visualize the challenge at hand is\u0000whack-a-mole governance, although the emerging solutions are perhaps not so\u0000different either.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139665653","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}
Claire L. Little, David M. Schultz, Belay B. Yimer, Anna L. Beukenhorst
Although many people believe their pain fluctuates with weather conditions, both weather and pain may be associated with time spent outside. For example, pleasant weather may mean that people spend more time outside doing physical activity and exposed to the weather, leading to more (or less) pain, and poor weather or severe pain may keep people inside, sedentary, and not exposed to the weather. We conducted a smartphone study where participants with chronic pain reported daily pain severity, as well as time spent outside. We address the relationship between four weather variables (temperature, dewpoint temperature, pressure, and wind speed) and pain by proposing a three-step approach to untangle their effects: (i) propose a set of plausible directed acyclic graphs (also known as DAGs) that account for potential roles of time spent outside (e.g., collider, effect modifier, mediator), (ii) analyze the compatibility of the observed data with the assumed model, and (iii) identify the most plausible model by combining evidence from the observed data and domain-specific knowledge. We found that the data do not support time spent outside as a collider or mediator of the relationship between weather variables and pain. On the other hand, time spent outside modifies the effect between temperature and pain, as well as wind speed and pain, with the effect being absent on days that participants spent inside and present if they spent some or all of the day outside. Our results show the utility of using directed acyclic graphs for studying causal inference.
{"title":"How Being Inside or Outside of Buildings Affects the Causal Relationship Between Weather and Pain Among People Living with Chronic Pain","authors":"Claire L. Little, David M. Schultz, Belay B. Yimer, Anna L. Beukenhorst","doi":"arxiv-2401.17678","DOIUrl":"https://doi.org/arxiv-2401.17678","url":null,"abstract":"Although many people believe their pain fluctuates with weather conditions,\u0000both weather and pain may be associated with time spent outside. For example,\u0000pleasant weather may mean that people spend more time outside doing physical\u0000activity and exposed to the weather, leading to more (or less) pain, and poor\u0000weather or severe pain may keep people inside, sedentary, and not exposed to\u0000the weather. We conducted a smartphone study where participants with chronic\u0000pain reported daily pain severity, as well as time spent outside. We address\u0000the relationship between four weather variables (temperature, dewpoint\u0000temperature, pressure, and wind speed) and pain by proposing a three-step\u0000approach to untangle their effects: (i) propose a set of plausible directed\u0000acyclic graphs (also known as DAGs) that account for potential roles of time\u0000spent outside (e.g., collider, effect modifier, mediator), (ii) analyze the\u0000compatibility of the observed data with the assumed model, and (iii) identify\u0000the most plausible model by combining evidence from the observed data and\u0000domain-specific knowledge. We found that the data do not support time spent\u0000outside as a collider or mediator of the relationship between weather variables\u0000and pain. On the other hand, time spent outside modifies the effect between\u0000temperature and pain, as well as wind speed and pain, with the effect being\u0000absent on days that participants spent inside and present if they spent some or\u0000all of the day outside. Our results show the utility of using directed acyclic\u0000graphs for studying causal inference.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139657971","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}
Martha Lorena Avendaño-Garrido, Carlos Alberto Hernández-Linares, Brenda Zarahí Medina-Pérez, Varsovia Hernández, Porfirio Toledo, Alejandro León
This study proposes an innovative approach to analyze spatial patterns of behavior by integrating information in weighted Voronoi diagrams. The objective of the research is to analyze the temporal distribution of an experimental subject in different regions of a given space, with the aim of identifying significant areas of interest. The methodology employed involves dividing the experimental space, determining representative points, and assigning weights based on the cumulative time the subject spends in each region. This process results in a set of generator points along with their respective weights, thus defining the Voronoi diagram. The study also presents a detailed and advanced perspective for understanding spatial behavioral patterns in experimental contexts.
{"title":"Identification of spatial dynamic patterns of behavior using weighted Voronoi diagrams","authors":"Martha Lorena Avendaño-Garrido, Carlos Alberto Hernández-Linares, Brenda Zarahí Medina-Pérez, Varsovia Hernández, Porfirio Toledo, Alejandro León","doi":"arxiv-2401.17411","DOIUrl":"https://doi.org/arxiv-2401.17411","url":null,"abstract":"This study proposes an innovative approach to analyze spatial patterns of\u0000behavior by integrating information in weighted Voronoi diagrams. The objective\u0000of the research is to analyze the temporal distribution of an experimental\u0000subject in different regions of a given space, with the aim of identifying\u0000significant areas of interest. The methodology employed involves dividing the\u0000experimental space, determining representative points, and assigning weights\u0000based on the cumulative time the subject spends in each region. This process\u0000results in a set of generator points along with their respective weights, thus\u0000defining the Voronoi diagram. The study also presents a detailed and advanced\u0000perspective for understanding spatial behavioral patterns in experimental\u0000contexts.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139657969","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}
C. A. Saez, M. G. Lobos, E. C. Macaya, D. Oliva, W. Quiroz, M. T. Brown
Seaweeds are well known to concentrate metals from seawater and have been employed as monitors of metal pollution in coastal waters and estuaries. However, research showing that various intrinsic and extrinsic factors can influence metal accumulation, raises doubts about the basis for using seaweeds in biomonitoring programmes. The thallus of brown seaweeds of the order Laminariales (kelps) is morphologically complex but there is limited information about the variation in metal accumulation between the different parts, which might result in erroneous conclusions being drawn if not accounted for in the biomonitoring protocol. To assess patterns of individual metals in the differentiated parts of the thallus (blade, stipe, holdfast), concentrations of a wide range of essential and non-essential metals (Fe, Cr, Cu, Zn, Mn, Pb, Cd, Ni and Al) were measured in the kelp Lessonia trabeculata. Seaweeds were collected from three sampling stations located at 5, 30 and 60 m from an illegal sewage outfall close to Ventanas, Chile and from a pristine location at Faro Curaumilla. For the majority of metals the highest concentrations in bottom sediment and seaweed samples were found at the site closest to the outfall, with concentrations decreasing with distance from the outfall and at control stations; the exception was Cd, concentrations of which were higher at control stations. The patterns of metal concentrations in different thallus parts were metal specific and independent of sampling station. These results and the available literature suggest that biomonitoring of metals using seaweeds must take account of differences in the accumulation of metals in thallus parts of complex seaweeds
{"title":"Variation in Patterns of Metal Accumulation in Thallus Parts of Lessonia trabeculata (Laminariales; Phaeophyceae): Implications for Biomonitoring","authors":"C. A. Saez, M. G. Lobos, E. C. Macaya, D. Oliva, W. Quiroz, M. T. Brown","doi":"arxiv-2401.17325","DOIUrl":"https://doi.org/arxiv-2401.17325","url":null,"abstract":"Seaweeds are well known to concentrate metals from seawater and have been\u0000employed as monitors of metal pollution in coastal waters and estuaries.\u0000However, research showing that various intrinsic and extrinsic factors can\u0000influence metal accumulation, raises doubts about the basis for using seaweeds\u0000in biomonitoring programmes. The thallus of brown seaweeds of the order\u0000Laminariales (kelps) is morphologically complex but there is limited\u0000information about the variation in metal accumulation between the different\u0000parts, which might result in erroneous conclusions being drawn if not accounted\u0000for in the biomonitoring protocol. To assess patterns of individual metals in\u0000the differentiated parts of the thallus (blade, stipe, holdfast),\u0000concentrations of a wide range of essential and non-essential metals (Fe, Cr,\u0000Cu, Zn, Mn, Pb, Cd, Ni and Al) were measured in the kelp Lessonia trabeculata.\u0000Seaweeds were collected from three sampling stations located at 5, 30 and 60 m\u0000from an illegal sewage outfall close to Ventanas, Chile and from a pristine\u0000location at Faro Curaumilla. For the majority of metals the highest\u0000concentrations in bottom sediment and seaweed samples were found at the site\u0000closest to the outfall, with concentrations decreasing with distance from the\u0000outfall and at control stations; the exception was Cd, concentrations of which\u0000were higher at control stations. The patterns of metal concentrations in\u0000different thallus parts were metal specific and independent of sampling\u0000station. These results and the available literature suggest that biomonitoring\u0000of metals using seaweeds must take account of differences in the accumulation\u0000of metals in thallus parts of complex seaweeds","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"77 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139657974","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}
Peter Bajcsy, Sreenivas Bhattiprolu, Katy Borner, Beth Cimini, Lucy Collinson, Jan Ellenberg, Reto Fiolka, Maryellen Giger, Wojtek Goscinski, Matthew Hartley, Nathan Hotaling, Rick Horwitz, Florian Jug, Anna Kreshuk, Emma Lundberg, Aastha Mathur, Kedar Narayan, Shuichi Onami, Anne L. Plant, Fred Prior, Jason Swedlow, Adam Taylor, Antje Keppler
Coordinated collaboration is essential to realize the added value of and infrastructure requirements for global image data sharing in the life sciences. In this White Paper, we take a first step at presenting some of the most common use cases as well as critical/emerging use cases of (including the use of artificial intelligence for) biological and medical image data, which would benefit tremendously from better frameworks for sharing (including technical, resourcing, legal, and ethical aspects). In the second half of this paper, we paint an ideal world scenario for how global image data sharing could work and benefit all life sciences and beyond. As this is still a long way off, we conclude by suggesting several concrete measures directed toward our institutions, existing imaging communities and data initiatives, and national funders, as well as publishers. Our vision is that within the next ten years, most researchers in the world will be able to make their datasets openly available and use quality image data of interest to them for their research and benefit. This paper is published in parallel with a companion White Paper entitled Harmonizing the Generation and Pre-publication Stewardship of FAIR Image Data, which addresses challenges and opportunities related to producing well-documented and high-quality image data that is ready to be shared. The driving goal is to address remaining challenges and democratize access to everyday practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.
{"title":"Enabling Global Image Data Sharing in the Life Sciences","authors":"Peter Bajcsy, Sreenivas Bhattiprolu, Katy Borner, Beth Cimini, Lucy Collinson, Jan Ellenberg, Reto Fiolka, Maryellen Giger, Wojtek Goscinski, Matthew Hartley, Nathan Hotaling, Rick Horwitz, Florian Jug, Anna Kreshuk, Emma Lundberg, Aastha Mathur, Kedar Narayan, Shuichi Onami, Anne L. Plant, Fred Prior, Jason Swedlow, Adam Taylor, Antje Keppler","doi":"arxiv-2401.13023","DOIUrl":"https://doi.org/arxiv-2401.13023","url":null,"abstract":"Coordinated collaboration is essential to realize the added value of and\u0000infrastructure requirements for global image data sharing in the life sciences.\u0000In this White Paper, we take a first step at presenting some of the most common\u0000use cases as well as critical/emerging use cases of (including the use of\u0000artificial intelligence for) biological and medical image data, which would\u0000benefit tremendously from better frameworks for sharing (including technical,\u0000resourcing, legal, and ethical aspects). In the second half of this paper, we\u0000paint an ideal world scenario for how global image data sharing could work and\u0000benefit all life sciences and beyond. As this is still a long way off, we\u0000conclude by suggesting several concrete measures directed toward our\u0000institutions, existing imaging communities and data initiatives, and national\u0000funders, as well as publishers. Our vision is that within the next ten years,\u0000most researchers in the world will be able to make their datasets openly\u0000available and use quality image data of interest to them for their research and\u0000benefit. This paper is published in parallel with a companion White Paper\u0000entitled Harmonizing the Generation and Pre-publication Stewardship of FAIR\u0000Image Data, which addresses challenges and opportunities related to producing\u0000well-documented and high-quality image data that is ready to be shared. The\u0000driving goal is to address remaining challenges and democratize access to\u0000everyday practices and tools for a spectrum of biomedical researchers,\u0000regardless of their expertise, access to resources, and geographical location.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139554074","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}
Nikki BialySteven, Frank AlberSteven, Brenda AndrewsSteven, Michael AngeloSteven, Brian BeliveauSteven, Lacramioara BintuSteven, Alistair BoettigerSteven, Ulrike BoehmSteven, Claire M. BrownSteven, Mahmoud Bukar MainaSteven, James J. ChambersSteven, Beth CiminiSteven, Kevin EliceiriSteven, Rachel ErringtonSteven, Orestis FaklarisSteven, Nathalie GaudreaultSteven, Ronald N. GermainSteven, Wojtek GoscinskiSteven, David GrunwaldSteven, Michael HalterSteven, Dorit HaneinSteven, John W. HickeySteven, Judith LacosteSteven, Alex LaudeSteven, Emma LundbergSteven, Jian MaSteven, Leonel MalacridaSteven, Josh MooreSteven, Glyn NelsonSteven, Elizabeth Kathleen NeumannSteven, Roland NitschkeSteven, Shichi OnamiSteven, Jaime A. PimentelSteven, Anne L. PlantSteven, Andrea J. RadtkeSteven, Bikash SabataSteven, Denis SchapiroSteven, Johannes SchönebergSteven, Jeffrey M. SpragginsSteven, Damir SudarSteven, Wouter-Michiel Adrien Maria VierdagSteven, Niels VolkmannSteven, Carolina WählbySteven, SiyuanSteven, Wang, Ziv Yaniv, Caterina Strambio-De-Castillia
Together with the molecular knowledge of genes and proteins, biological images promise to significantly enhance the scientific understanding of complex cellular systems and to advance predictive and personalized therapeutic products for human health. For this potential to be realized, quality-assured image data must be shared among labs at a global scale to be compared, pooled, and reanalyzed, thus unleashing untold potential beyond the original purpose for which the data was generated. There are two broad sets of requirements to enable image data sharing in the life sciences. One set of requirements is articulated in the companion White Paper entitled Enabling Global Image Data Sharing in the Life Sciences, which is published in parallel and addresses the need to build the cyberinfrastructure for sharing the digital array data. In this White Paper, we detail a broad set of requirements, which involves collecting, managing, presenting, and propagating contextual information essential to assess the quality, understand the content, interpret the scientific implications, and reuse image data in the context of the experimental details. We start by providing an overview of the main lessons learned to date through international community activities, which have recently made considerable progress toward generating community standard practices for imaging Quality Control (QC) and metadata. We then provide a clear set of recommendations for amplifying this work. The driving goal is to address remaining challenges and democratize access to everyday practices and tools for a spectrum of biomedical researchers, regardless of their expertise, access to resources, and geographical location.
{"title":"Harmonizing the Generation and Pre-publication Stewardship of FAIR Image Data","authors":"Nikki BialySteven, Frank AlberSteven, Brenda AndrewsSteven, Michael AngeloSteven, Brian BeliveauSteven, Lacramioara BintuSteven, Alistair BoettigerSteven, Ulrike BoehmSteven, Claire M. BrownSteven, Mahmoud Bukar MainaSteven, James J. ChambersSteven, Beth CiminiSteven, Kevin EliceiriSteven, Rachel ErringtonSteven, Orestis FaklarisSteven, Nathalie GaudreaultSteven, Ronald N. GermainSteven, Wojtek GoscinskiSteven, David GrunwaldSteven, Michael HalterSteven, Dorit HaneinSteven, John W. HickeySteven, Judith LacosteSteven, Alex LaudeSteven, Emma LundbergSteven, Jian MaSteven, Leonel MalacridaSteven, Josh MooreSteven, Glyn NelsonSteven, Elizabeth Kathleen NeumannSteven, Roland NitschkeSteven, Shichi OnamiSteven, Jaime A. PimentelSteven, Anne L. PlantSteven, Andrea J. RadtkeSteven, Bikash SabataSteven, Denis SchapiroSteven, Johannes SchönebergSteven, Jeffrey M. SpragginsSteven, Damir SudarSteven, Wouter-Michiel Adrien Maria VierdagSteven, Niels VolkmannSteven, Carolina WählbySteven, SiyuanSteven, Wang, Ziv Yaniv, Caterina Strambio-De-Castillia","doi":"arxiv-2401.13022","DOIUrl":"https://doi.org/arxiv-2401.13022","url":null,"abstract":"Together with the molecular knowledge of genes and proteins, biological\u0000images promise to significantly enhance the scientific understanding of complex\u0000cellular systems and to advance predictive and personalized therapeutic\u0000products for human health. For this potential to be realized, quality-assured\u0000image data must be shared among labs at a global scale to be compared, pooled,\u0000and reanalyzed, thus unleashing untold potential beyond the original purpose\u0000for which the data was generated. There are two broad sets of requirements to\u0000enable image data sharing in the life sciences. One set of requirements is\u0000articulated in the companion White Paper entitled Enabling Global Image Data\u0000Sharing in the Life Sciences, which is published in parallel and addresses the\u0000need to build the cyberinfrastructure for sharing the digital array data. In\u0000this White Paper, we detail a broad set of requirements, which involves\u0000collecting, managing, presenting, and propagating contextual information\u0000essential to assess the quality, understand the content, interpret the\u0000scientific implications, and reuse image data in the context of the\u0000experimental details. We start by providing an overview of the main lessons\u0000learned to date through international community activities, which have recently\u0000made considerable progress toward generating community standard practices for\u0000imaging Quality Control (QC) and metadata. We then provide a clear set of\u0000recommendations for amplifying this work. The driving goal is to address\u0000remaining challenges and democratize access to everyday practices and tools for\u0000a spectrum of biomedical researchers, regardless of their expertise, access to\u0000resources, and geographical location.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139554109","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}
Eleanor Dunlop, Judy Cunningham, Paul Adorno, Georgios Dabos, Stuart K Johnson, Lucinda J Black
Vitamin K is emerging as a multi-function vitamin that plays a role in bone, brain and vascular health. Vitamin K composition data remain limited globally and Australia has lacked nationally representative data for vitamin K1 (phylloquinone, PK) in horticultural commodities. Primary samples (n = 927) of 90 different Australian-grown fruit, vegetable and nut commodities were purchased in three Australian cities. We measured PK in duplicate in 95 composite samples using liquid chromatography with electrospray ionisation-tandem mass spectrometry. The greatest mean concentrations of PK were found in kale (565 ug/100 g), baby spinach (255 ug/100 g) and Brussels sprouts (195 ug/100 g). The data contribute to the global collection of vitamin K food composition data. They add to the evidence that PK concentrations vary markedly between geographic regions, supporting development of region-specific datasets for national food composition databases that do not yet contain data for vitamin K.
维生素 K 是一种新兴的多功能维生素，在骨骼、大脑和血管健康方面发挥着作用。全球的维生素 K 成分数据仍然有限，而澳大利亚一直缺乏园艺产品中维生素 K1（植物喹啉酮，PK）的全国代表性数据。我们在澳大利亚的三个城市购买了 90 种不同的澳大利亚种植的水果、蔬菜和坚果的初级样品（n = 927）。我们采用液相色谱-电喷雾串联质谱法对 95 份复合样品中的 PK 进行了重复测定。羽衣甘蓝（565 微克/100 克）、小菠菜（255 微克/100 克）和球芽甘蓝（195 微克/100 克）中的 PK 平均浓度最高。这些数据为全球收集维生素K食物成分数据做出了贡献。这些数据进一步证明了不同地理区域之间的 PK 浓度存在显著差异，从而为尚未包含维生素 K 数据的国家食物成分数据库开发特定区域的数据集提供了支持。
{"title":"Vitamin K content of Australian-grown horticultural commodities","authors":"Eleanor Dunlop, Judy Cunningham, Paul Adorno, Georgios Dabos, Stuart K Johnson, Lucinda J Black","doi":"arxiv-2401.07473","DOIUrl":"https://doi.org/arxiv-2401.07473","url":null,"abstract":"Vitamin K is emerging as a multi-function vitamin that plays a role in bone,\u0000brain and vascular health. Vitamin K composition data remain limited globally\u0000and Australia has lacked nationally representative data for vitamin K1\u0000(phylloquinone, PK) in horticultural commodities. Primary samples (n = 927) of\u000090 different Australian-grown fruit, vegetable and nut commodities were\u0000purchased in three Australian cities. We measured PK in duplicate in 95\u0000composite samples using liquid chromatography with electrospray\u0000ionisation-tandem mass spectrometry. The greatest mean concentrations of PK\u0000were found in kale (565 ug/100 g), baby spinach (255 ug/100 g) and Brussels\u0000sprouts (195 ug/100 g). The data contribute to the global collection of vitamin\u0000K food composition data. They add to the evidence that PK concentrations vary\u0000markedly between geographic regions, supporting development of region-specific\u0000datasets for national food composition databases that do not yet contain data\u0000for vitamin K.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139481688","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}
Richard J. Abdill, Emma Talarico, Laura Grieneisen
Computational biology continues to spread into new fields, becoming more accessible to researchers trained in the wet lab who are eager to take advantage of growing datasets, falling costs, and novel assays that present new opportunities for discovery even outside of the much-discussed developments in artificial intelligence. However, guidance for implementing these techniques is much easier to find than guidance for reporting their use, leaving biologists to guess which details and files are relevant. Here, we provide a set of recommendations for sharing code, with an eye toward guiding those who are comparatively new to applying open science principles to their computational work. Additionally, we review existing literature on the topic, summarize the most common tips, and evaluate the code-sharing policies of the most influential journals in biology, which occasionally encourage code-sharing but seldom require it. Taken together, we provide a user manual for biologists who seek to follow code-sharing best practices but are unsure where to start.
{"title":"A how-to guide for code-sharing in biology","authors":"Richard J. Abdill, Emma Talarico, Laura Grieneisen","doi":"arxiv-2401.03068","DOIUrl":"https://doi.org/arxiv-2401.03068","url":null,"abstract":"Computational biology continues to spread into new fields, becoming more\u0000accessible to researchers trained in the wet lab who are eager to take\u0000advantage of growing datasets, falling costs, and novel assays that present new\u0000opportunities for discovery even outside of the much-discussed developments in\u0000artificial intelligence. However, guidance for implementing these techniques is\u0000much easier to find than guidance for reporting their use, leaving biologists\u0000to guess which details and files are relevant. Here, we provide a set of\u0000recommendations for sharing code, with an eye toward guiding those who are\u0000comparatively new to applying open science principles to their computational\u0000work. Additionally, we review existing literature on the topic, summarize the\u0000most common tips, and evaluate the code-sharing policies of the most\u0000influential journals in biology, which occasionally encourage code-sharing but\u0000seldom require it. Taken together, we provide a user manual for biologists who\u0000seek to follow code-sharing best practices but are unsure where to start.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139408231","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}
Analyzing the codon usage frequencies of a specimen of 20 plants, for which the codon-anticodon pattern is known, we have remarked that the hierarchy of the usage frequencies present an almost "universal" behavior. Searching to explain this behavior, we assume that the codon usage probability results from the sum of two contributions: the first dominant term is an almost "universal" one and it depends on the codon-anticodon interaction; the second term is a local one, i.e. depends on the biological species. The codon-anticodon interaction is written as a spin-spin plus a z-spin term in the formalism of the crystal basis model. From general considerations, in particular from the choice of the signs and some constraints on the parameters defining the interaction, we are able to explain most of the observed data.
{"title":"Hierarchy of codon usage frequencies from codon-anticodon interaction in the crystal basis model","authors":"Antonino Sciarrino, Paul Sorba","doi":"arxiv-2312.11107","DOIUrl":"https://doi.org/arxiv-2312.11107","url":null,"abstract":"Analyzing the codon usage frequencies of a specimen of 20 plants, for which\u0000the codon-anticodon pattern is known, we have remarked that the hierarchy of\u0000the usage frequencies present an almost \"universal\" behavior. Searching to\u0000explain this behavior, we assume that the codon usage probability results from\u0000the sum of two contributions: the first dominant term is an almost \"universal\"\u0000one and it depends on the codon-anticodon interaction; the second term is a\u0000local one, i.e. depends on the biological species. The codon-anticodon\u0000interaction is written as a spin-spin plus a z-spin term in the formalism of\u0000the crystal basis model. From general considerations, in particular from the\u0000choice of the signs and some constraints on the parameters defining the\u0000interaction, we are able to explain most of the observed data.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138742035","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}
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