"Leaders and Laggards in the preservation of raw biomedical research data" presented at NEDCC 2010, The Tectonics of Digital Curation
A Symposium on the Shifting Preservation and Access Landscape
Presented at ASIS&T 2009 in the student awards section. The presentation contains an overview of my dissertation proposal, as 2009 winner of the Thomson Reuters Information Science Doctoral Dissertation Proposal Scholarship, administered by the ASIS&T Information Science Education Committee
Scott Edmunds from GigaScience on 'Publishing in the Open Data Era", at the "Open, Crowdsource and Blockchain Science!" hangout at Hackerspace.sg, 23rd March 2015
High throughput mining of the scholarly literature; talk at NIHpetermurrayrust
The scientific and medical literature contains huge amounts of valuable unused information. This talk shows how to discover it, extract, re-use and interpret it. Wikidata is presented as a key new tool and infrastructure. Everyone can become involved. However some of the barriers to use are sociopolitical and these are identified and discussed.
Towards Responsible Content Mining: A Cambridge perspectivepetermurrayrust
ContentMining (Text and Data Mining) is now legal in the UK for non-commercial research. Cambridge UK is a natural centre, with several components:
* a world-class University and Library
* many publishers, both Open Access and conventional
* a digital culture
* ContentMine - a leading proponent and practitioner of mining
Cambridge University Press welcomes content mining and invited PMR to give a talk there. He showed the technology and protocols and proposed a practical way forward in 2017
Presented at ASIS&T 2009 in the student awards section. The presentation contains an overview of my dissertation proposal, as 2009 winner of the Thomson Reuters Information Science Doctoral Dissertation Proposal Scholarship, administered by the ASIS&T Information Science Education Committee
Scott Edmunds from GigaScience on 'Publishing in the Open Data Era", at the "Open, Crowdsource and Blockchain Science!" hangout at Hackerspace.sg, 23rd March 2015
High throughput mining of the scholarly literature; talk at NIHpetermurrayrust
The scientific and medical literature contains huge amounts of valuable unused information. This talk shows how to discover it, extract, re-use and interpret it. Wikidata is presented as a key new tool and infrastructure. Everyone can become involved. However some of the barriers to use are sociopolitical and these are identified and discussed.
Towards Responsible Content Mining: A Cambridge perspectivepetermurrayrust
ContentMining (Text and Data Mining) is now legal in the UK for non-commercial research. Cambridge UK is a natural centre, with several components:
* a world-class University and Library
* many publishers, both Open Access and conventional
* a digital culture
* ContentMine - a leading proponent and practitioner of mining
Cambridge University Press welcomes content mining and invited PMR to give a talk there. He showed the technology and protocols and proposed a practical way forward in 2017
Invited talk given at The Natural History Museum, London, 17 March 2009 (I gave a very similar talk at the Department of Zoology, University of Stockholm, 12 March 2009).
A Global Commons for Scientific Data: Molecules and Wikidatapetermurrayrust
Methods for extracting facts from the scientific literature, and linking them to Wikidata IDs. Wikidata is introduced by an architectural example and bioscience. Then we explore how data can be extracted from text and from images
Thesis defense, Heather Piwowar, Sharing biomedical research dataHeather Piwowar
Presentation by Heather Piwowar as PhD dissertation defense on March 24, 2010 at the Dept of Biomedical Informatics, U of Pittsburgh. "Foundational studies for
measuring the impact, prevalence, and patterns of publicly sharing biomedical research data." I passed :)
Digital Scholarship: Enlightenment or Devastated Landscape? TheContentMine
Published on Dec 17, 2015 by PMR
Every year 500 Billion USD of public funding is spent on research, but much of this lies hidden in papers that are never read. I describe how machines can help us to read the literature. However there is massive opposition from publishers who are trying to prevent open scholarship and who build walled gardens that they control
The increasing availability of free and open access resources for scientists on the internet presents us with a revolution in data availability. The Royal Society of Chemistry hosts ChemSpider, a free access website for chemists built with the intention of building community for chemists (http://www.chemspider.com/).
ChemSpider is an aggregator of chemistry related information, at present over 20 million unique chemical entities linked out to over 300 separate data sources, ChemSpider has taken on the task of both robotically and manually curating publicly available data sources. It is also a public deposition platform where chemists can deposit their own data including novel structures, analytical data, synthesis procedures and host data associated with the growing activities associated with Open Notebook Science.
This presentation will examine chemistry on the internet, the dubious quality of what is available and how the ChemSpider crowdsourced curation platform is fast becoming one of the centralized hubs for resourcing information about chemical entities.
We will also review our efforts to provide free resources for synthesis procedures, spectral data and structure-based searching of the chemistry literature and how chemists can contribute directly to each of these projects.
Weller social media as research data_psm15Katrin Weller
Presentation at "Preserving Social Media" (#psm15), London, October 27th 2015.
http://dpconline.org/events/details/96-preserving-socialmedia?xref=126%3ASocialMedia15
2014 CrossRef Annual Meeting Keynote: Ways and Needs to Promote Rapid Data Sh...Crossref
Keynote address: "Ways and Needs to Promote Rapid Data Sharing" by Laurie Goodman of GigaScience.
Data is the base upon which all scientific discoveries are built, and data availability speeds the rate at which discoveries are made. Given that the overall goal for research is to improve human health and our environment, waiting to release data until after the first publication (sometimes taking years) is unacceptable. There are myriad issues that impede researchers from openly, and most importantly, rapidly sharing data, including lack of incentives: no credit, limited funding benefits, and little impact on career advancement; and cultural issues: the fear of being scooped. However, scientific publishers —the communicators of science and a key mechanism by which a researcher’s productivity is measured— can, and should, play a central role in promoting data sharing. Data citation and publication are just some of the ways we can support and encourage researchers who share data. Here, I will provide examples to help make clear the need for publishers to play an active role in this process and provide potential ways to facilitate our ability to promote open and rapid data sharing. This is not easy; but it is essential.
Marco Brandizi and Keywan Hassani-Pak, Rothamsted Research, Invited Presentation at SWAT4HCLS 2022.
FAIR data principles are being a driving force in life sciences and other scientific domains, helping researchers to share their data and free all of their potential to integrate information and do novel discoveries. Knowledge graphs are an ever more popular paradigm to model data according to such principles, and technologies such as graph databases are emerging as complementary to approaches like linked data. All of this includes the agronomy, farming and food domains. How advanced the adoption of sound data management policies is in these life domains? How does that compare to other life sciences? In this presentation, we will talk about our practical experience, focusing on KnetMiner, a gene and molecular biology discovering platform, which is based on building and publishing knowledge graphs according to the FAIR principles, as well as using a mix of linked data standards for life sciences and recent graph database and API technologies. We will welcome questions and discussions from the audience about similar experience.
Scott Edmunds talk at AIST: Overcoming the Reproducibility Crisis: and why I ...GigaScience, BGI Hong Kong
Scott Edmunds talk at the AIST Computational Biology Research Center in Tokyo: Overcoming the Reproducibility Crisis: and why I stopped worrying a learned to love open data (& methods), July 1st 2014
How open data contribute to improving the world. The life science use case. The technical, social, ethical issues.
This was a talk given within the iGEM 2020 programme by the London Imperial College students group (https://2020.igem.org/Team:Imperial_College), in a webinar organised by the SOAPLab group on the topic of Ethics of Automation. Excellent Dr Brandon Sepulvado was the other speaker of the day.
searching tips and tools, recommendations, getting the most from databases, finding RCTs, EBP, evidence based practice, hospital library, DeepWeb, Grey Literature, Altmetrics,
Automatic Extraction of Knowledge from the LiteratureTheContentMine
Published on May 11, 2016 by PMR
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Opportunities and challenges presented by Wikidata in the context of biocurationBenjamin Good
Abstract—Wikidata is a world readable and writable knowledge base maintained by the Wikimedia Foundation. It offers the opportunity to collaboratively construct a fully open access knowledge graph spanning biology, medicine, and all other domains of knowledge. To meet this potential, social and technical challenges must be overcome - many of which are familiar to the biocuration community. These include community ontology building, high precision information extraction, provenance, and license management. By working together with Wikidata now, we can help shape it into a trustworthy, unencumbered central node in the Semantic Web of biomedical data.
Published on May 18, 2016 by PMR
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Text Mining Rights from Three Perspectives: Researcher.Heather Piwowar
Presentation by Heather Piwowar at the Charleston Conference 2012 as part of the "Text Mining Rights from Three Perspectives" session with Teresa Lee and Judson Dunham
http://2012charlestonconference.sched.org/event/fefb0c29aa6bbf91521e35efc2dd151c
See Jud's slides at http://www.slideshare.net/judsondunham/three-perspectives-on-text-mining-publisher
Invited talk given at The Natural History Museum, London, 17 March 2009 (I gave a very similar talk at the Department of Zoology, University of Stockholm, 12 March 2009).
A Global Commons for Scientific Data: Molecules and Wikidatapetermurrayrust
Methods for extracting facts from the scientific literature, and linking them to Wikidata IDs. Wikidata is introduced by an architectural example and bioscience. Then we explore how data can be extracted from text and from images
Thesis defense, Heather Piwowar, Sharing biomedical research dataHeather Piwowar
Presentation by Heather Piwowar as PhD dissertation defense on March 24, 2010 at the Dept of Biomedical Informatics, U of Pittsburgh. "Foundational studies for
measuring the impact, prevalence, and patterns of publicly sharing biomedical research data." I passed :)
Digital Scholarship: Enlightenment or Devastated Landscape? TheContentMine
Published on Dec 17, 2015 by PMR
Every year 500 Billion USD of public funding is spent on research, but much of this lies hidden in papers that are never read. I describe how machines can help us to read the literature. However there is massive opposition from publishers who are trying to prevent open scholarship and who build walled gardens that they control
The increasing availability of free and open access resources for scientists on the internet presents us with a revolution in data availability. The Royal Society of Chemistry hosts ChemSpider, a free access website for chemists built with the intention of building community for chemists (http://www.chemspider.com/).
ChemSpider is an aggregator of chemistry related information, at present over 20 million unique chemical entities linked out to over 300 separate data sources, ChemSpider has taken on the task of both robotically and manually curating publicly available data sources. It is also a public deposition platform where chemists can deposit their own data including novel structures, analytical data, synthesis procedures and host data associated with the growing activities associated with Open Notebook Science.
This presentation will examine chemistry on the internet, the dubious quality of what is available and how the ChemSpider crowdsourced curation platform is fast becoming one of the centralized hubs for resourcing information about chemical entities.
We will also review our efforts to provide free resources for synthesis procedures, spectral data and structure-based searching of the chemistry literature and how chemists can contribute directly to each of these projects.
Weller social media as research data_psm15Katrin Weller
Presentation at "Preserving Social Media" (#psm15), London, October 27th 2015.
http://dpconline.org/events/details/96-preserving-socialmedia?xref=126%3ASocialMedia15
2014 CrossRef Annual Meeting Keynote: Ways and Needs to Promote Rapid Data Sh...Crossref
Keynote address: "Ways and Needs to Promote Rapid Data Sharing" by Laurie Goodman of GigaScience.
Data is the base upon which all scientific discoveries are built, and data availability speeds the rate at which discoveries are made. Given that the overall goal for research is to improve human health and our environment, waiting to release data until after the first publication (sometimes taking years) is unacceptable. There are myriad issues that impede researchers from openly, and most importantly, rapidly sharing data, including lack of incentives: no credit, limited funding benefits, and little impact on career advancement; and cultural issues: the fear of being scooped. However, scientific publishers —the communicators of science and a key mechanism by which a researcher’s productivity is measured— can, and should, play a central role in promoting data sharing. Data citation and publication are just some of the ways we can support and encourage researchers who share data. Here, I will provide examples to help make clear the need for publishers to play an active role in this process and provide potential ways to facilitate our ability to promote open and rapid data sharing. This is not easy; but it is essential.
Marco Brandizi and Keywan Hassani-Pak, Rothamsted Research, Invited Presentation at SWAT4HCLS 2022.
FAIR data principles are being a driving force in life sciences and other scientific domains, helping researchers to share their data and free all of their potential to integrate information and do novel discoveries. Knowledge graphs are an ever more popular paradigm to model data according to such principles, and technologies such as graph databases are emerging as complementary to approaches like linked data. All of this includes the agronomy, farming and food domains. How advanced the adoption of sound data management policies is in these life domains? How does that compare to other life sciences? In this presentation, we will talk about our practical experience, focusing on KnetMiner, a gene and molecular biology discovering platform, which is based on building and publishing knowledge graphs according to the FAIR principles, as well as using a mix of linked data standards for life sciences and recent graph database and API technologies. We will welcome questions and discussions from the audience about similar experience.
Scott Edmunds talk at AIST: Overcoming the Reproducibility Crisis: and why I ...GigaScience, BGI Hong Kong
Scott Edmunds talk at the AIST Computational Biology Research Center in Tokyo: Overcoming the Reproducibility Crisis: and why I stopped worrying a learned to love open data (& methods), July 1st 2014
How open data contribute to improving the world. The life science use case. The technical, social, ethical issues.
This was a talk given within the iGEM 2020 programme by the London Imperial College students group (https://2020.igem.org/Team:Imperial_College), in a webinar organised by the SOAPLab group on the topic of Ethics of Automation. Excellent Dr Brandon Sepulvado was the other speaker of the day.
searching tips and tools, recommendations, getting the most from databases, finding RCTs, EBP, evidence based practice, hospital library, DeepWeb, Grey Literature, Altmetrics,
Automatic Extraction of Knowledge from the LiteratureTheContentMine
Published on May 11, 2016 by PMR
ContentMine tools (and the Harvest alliance) can be used to search the literature for knowledge, especially in biomedicine. All tools are Open and shortly we shall be indexing the complete daily scholarly literature
Opportunities and challenges presented by Wikidata in the context of biocurationBenjamin Good
Abstract—Wikidata is a world readable and writable knowledge base maintained by the Wikimedia Foundation. It offers the opportunity to collaboratively construct a fully open access knowledge graph spanning biology, medicine, and all other domains of knowledge. To meet this potential, social and technical challenges must be overcome - many of which are familiar to the biocuration community. These include community ontology building, high precision information extraction, provenance, and license management. By working together with Wikidata now, we can help shape it into a trustworthy, unencumbered central node in the Semantic Web of biomedical data.
Published on May 18, 2016 by PMR
Talk to EBI Industry group on Open Software for chemical and pharmaceutical sciences. Covers examples of chemistry , wit demos, and argues that all public knowledge should be Openly accessible
Text Mining Rights from Three Perspectives: Researcher.Heather Piwowar
Presentation by Heather Piwowar at the Charleston Conference 2012 as part of the "Text Mining Rights from Three Perspectives" session with Teresa Lee and Judson Dunham
http://2012charlestonconference.sched.org/event/fefb0c29aa6bbf91521e35efc2dd151c
See Jud's slides at http://www.slideshare.net/judsondunham/three-perspectives-on-text-mining-publisher
AAAS 2012: Data about the costs and benefits of Open Research DAtaHeather Piwowar
Heather Piwowar's talk at AAAS 2012 session on Accelerating Scientific Progress Through Public Availability of Research Data http://aaas.confex.com/aaas/2012/webprogram/Session4117.html
submission summary for #WSSSPE Policy session on Credit, Citation, and ImpactHeather Piwowar
submission summary for #WSSSPE Policy session on Credit, Citation, and Impact
presentation by Heather Piwowar
November 2013
agenda: http://wssspe.researchcomputing.org.uk/
Thesis Proposal, as presented for dissertation proposal defenseHeather Piwowar
The slides I presented for my PhD proposal defense for my project, "Foundational studies for measuring the impact, prevalence, and patterns of publicly sharing biomedical research data." Dept of Biomedical Informatics, University of Pittsburgh.
Laurie Goodman at #aibsdata: Beyond Data Release Mandates - Helping Authors M...GigaScience, BGI Hong Kong
Laurie Goodman at the AIBS Changing Practices in Data Pub workshop: Beyond Data Release Mandates - Helping Authors Make Data Available. 3rd December 2014
Why study Data Sharing? (+ why share your data)Heather Piwowar
A presentation to the DBMI department at the University of Pittsburgh about data sharing and reuse: what this means, why it is important, some of what we’ve learned, and what we still don’t know.
PLoS ONE Piwowar: Sharing Detailed Research Data Is Associated with Increa...Heather Piwowar
Heather A Piwowar, Roger S Day, Douglas B Fridsma (2007) Sharing Detailed Research Data Is Associated with Increased Citation Rate PLoS ONE 2: 3. e308
Abstract: Sharing research data provides benefit to the general scientific community, but the benefit is less obvious for the investigator who makes his or her data available. We examined the citation history of 85 cancer microarray clinical trial publications with respect to the availability of their data. The 48% of trials with publicly available microarray data received 85% of the aggregate citations. Publicly available data was significantly (p = 0.006) associated with a 69% increase in citations, independently of journal impact factor, date of publication, and author country of origin using linear regression. This correlation between publicly available data and increased literature impact may further motivate investigators to share their detailed research data.
Scott Edmunds slides for class 8 from the HKU Data Curation (module MLIM7350 from the Faculty of Education) course covering science data, medical data and ethics, and the FAIR data principles.
Scott Edmunds slides from class 7 from the HKU Data Curation (module MLIM7350 from the Faculty of Education) course covering open data policy and practice, and the Hong Kong context.
Developing data services: a tale from two Oregon universitiesAmanda Whitmire
While the generation or collection of large, complex research datasets is becoming easier and less expensive all the time, researchers often lack the knowledge and skills that are necessary to properly manage them. Having these skills is paramount in ensuring data quality, integrity, discoverability, integration, reproducibility, and reuse over time. Librarians have been preserving, managing and disseminating information for thousands of years. As scholarly research is increasingly carried out digitally, and products of research have expanded from primarily text-based manuscripts to include datasets, metadata, maps, software code etc., it is a natural expansion of scope for libraries to be involved in the stewardship of these materials as well. This kind of evolution requires that libraries bring in faculty with new skills and collaborate more intimately with researchers during the research data lifecycle, and this is exactly what is happening in academic libraries across the country. In this webinar, two researchers-turned-data-specialists, both based in academic libraries, will share their experiences and perspectives on the development of research data services at their respective institutions. Each will share their perspective on the important role that libraries can play in helping researchers manage, preserve, and share their data.
Laurie Goodman on "Overcoming Hurdles to Data Publication" for the Alan Turing Institute Symposium on Reproducibility for Data-Intensive Research, Oxford, 7th April 2016.
Who cares how research data is attributed and cited? Lots of people. Presented by Heather Piwowar to DataONE summer internship 2010 group on data citatio
Workshop finding and accessing data - fiona nadia charlotte - cambridge apr...Fiona Nielsen
Workshop presentation on finding and accessing human genomics data for research.
Including statistics of publicly available data sources and tips on how to save time in your workflow of data access.
Organised in collaboration between DNAdigest and Open Data Cambridge.
Read more about our work:
http://DNAdigest.org
http://repositive.io
https://uk.linkedin.com/in/fionanielsen
http://www.data.cam.ac.uk
Recomendations for infrastructure and incentives for open science, presented to the Research Data Alliance 6th Plenary. Presenter: William Gunn, Director of Scholarly Communications for Mendeley.
Open Data in a Big Data World: easy to say, but hard to do?LEARN Project
Presentation at 3rd LEARN workshop on Research Data Management, “Make research data management policies work”
Helsinki, 28 June 2016, by Sarah Callaghan, STFC Rutherford Appleton Laboratory
The Path to Open Science with Illustrations from Computational Biology - A presentation made at the Microsoft 2011 Latin America Faculty Summit Cartagena, Columbia, May 18, 2011.
Crowdsourcing applied to knowledge management in translational research: the ...SC CTSI at USC and CHLA
Date: November 8th, 2018
Speaker: Andrew Su, PhD, Professor, Department of Integrative, Structural and Computational Biology, The Scripps Research Institute
Overview: Crowdsourcing involves the engagement of large communities of individuals to collaboratively accomplish tasks at massive scale. These tasks could be online or offline, paid or for free. But how can crowdsourcing science help your research? This webinar will describe two crowdsourcing projects for translational research, both of which aim to better organize biomedical information so that it can be more easily accessed, integrated, and queried:
First, the goal of the Gene Wiki project is to create a community-maintained knowledge base of all relationships between biological entities, including genes, diseases, drugs, pathways, and variants. This project draws on the collective efforts of informatics researchers from a wide range of disciplines, including bioinformatics, cheminformatics, and medical informatics.
Second, the Mark2Cure project partners with the citizen scientist community to extract structured content from biomedical abstracts with an emphasis on rare disease. Although citizen scientists do not have any specialized expertise, after receiving proper training, Mark2Cure has shown that in aggregate they perform bio-curation at an accuracy comparable to professional scientists.
Introduction to Gene Mining Part A: BLASTn-off!adcobb
In this lesson, students will learn to use bioinformatics portals and tools to mine plant versions of human genes. Student handout and teacher resource materials are available at www.Araport.org, Teaching Resources (Community tab). Suitable for grades 9-12 or first year undergraduate students.
Similar to NEDCC 2010 Piwowar Leaders and Laggards (20)
Calculating how much your University spends on Open Access--and what to do ab...Heather Piwowar
#NASIG2020 presentation
Librarians are working hard to understand how much money their university is spending on open access article processing fees (APCs), and how much of what they subscribe to is available as OA. This information is useful when making subscription decisions, considering Read and Publish agreements, rethinking library open access budgets, and designing Institution-wide OA policies.
This session will talk concretely about how to calculate the impact of Open Access on *your* university. It will provide an overview on how to estimate the amount of money spent across a university on Open Access fees: we will discuss underlying concepts behind calculating OA article-processing fee (APC) spend and give an overview of useful data sources, including Unsub.
Follow at @unsub_org
How to Calculate OA APC Spend for Your UniversityHeather Piwowar
Universities are hungry to know how much they spend on Open Access fees. This data is important to planning transformative and read and publish agreements, forming library strategy, and understanding scholarly communication on your campus. Unfortunately, it hasn’t been easy to calculate how much your university is spending on Open Access.
Learn how recent developments in data sources and tools have made this easier during this webinar. We will discuss the underlying concepts behind calculating OA article-processing fee (APC) spend, and provide you with paths to calculate the Open Access fees paid by your institution. ALCTS webinar.
Intro to Managing Serials with Net Cost per Paid UseHeather Piwowar
This webinar will introduce a new metric for evaluating the cost effectiveness of Serials: Net Cost Per Paid Use (NCPPU). NCPPU goes beyond the standard Cost Per Use calculation to exclude free content (OA and back catalog), incorporate ILL costs, and value citation and authorship. ALCTS webinar.
Short version: Uncovering the Impact Story of ResearchHeather Piwowar
Presentation by Heather Piwowar at the Charleston Conference 2012 as part of the panel on Article Level Metrics: Analyzing Value in the Scholarly Content
http://2012charlestonconference.sched.org/event/3a0172c38ebc215b0d6eae7f6382c031
Qs for Charleston2012 Empowering Scholars through AltmetricsHeather Piwowar
Very basic slidedeck behind panel at Charleston Conference 2012 session on Empowering Scholars through Altmetrics
http://2012charlestonconference.sched.org/event/4189f2e95c3ba9b4bbeb1f8376a42dd9#.UKgEguOe-E4
Heather Piwowar webinar presentation to ANDS in Oct 2012 on data citation tracking metrics. Audio here: http://www.youtube.com/watch?v=oivka4JnjhA&feature=plcp
Presentation by Heather Piwowar at Simon Fraser University in October 2012 at the SFU Research Data Repository Project Launch.
Highlights current state of research data sharing. http://www.lib.sfu.ca/node/11510
NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
The prostate is an exocrine gland of the male mammalian reproductive system
It is a walnut-sized gland that forms part of the male reproductive system and is located in front of the rectum and just below the urinary bladder
Function is to store and secrete a clear, slightly alkaline fluid that constitutes 10-30% of the volume of the seminal fluid that along with the spermatozoa, constitutes semen
A healthy human prostate measures (4cm-vertical, by 3cm-horizontal, 2cm ant-post ).
It surrounds the urethra just below the urinary bladder. It has anterior, median, posterior and two lateral lobes
It’s work is regulated by androgens which are responsible for male sex characteristics
Generalised disease of the prostate due to hormonal derangement which leads to non malignant enlargement of the gland (increase in the number of epithelial cells and stromal tissue)to cause compression of the urethra leading to symptoms (LUTS
Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
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Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
- Video recording of this lecture in English language: https://youtu.be/lK81BzxMqdo
- Video recording of this lecture in Arabic language: https://youtu.be/Ve4P0COk9OI
- Link to download the book free: https://nephrotube.blogspot.com/p/nephrotube-nephrology-books.html
- Link to NephroTube website: www.NephroTube.com
- Link to NephroTube social media accounts: https://nephrotube.blogspot.com/p/join-nephrotube-on-social-media.html
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
Ocular injury ppt Upendra pal optometrist upums saifai etawah
NEDCC 2010 Piwowar Leaders and Laggards
1. Leaders and Laggards
in the preservation of
raw biomedical research data
Heather Piwowar
Department of Biomedical Informatics
University of Pittsburgh
Soon‐to‐be Postdoctoral Associate with
Data Observation Network for Earth (DataONE)
13. Researchers have a choice
PAST MEDICAL HISTORY:
Past medical history showed she had
superficial phlebitis times two in the past, had
non-insulin dependent diabetes mellitus for
four years.
She had been hypothyroid for three years.
HISTORY OF PRESENT ILLNESS:
The patient is a 58-year-old female, …
http://upload.wikimedia.org/wikipedia/commons/7/76/PeptideMSMS.jpg; http://en.wikipedia.org/wiki/Image:Helices.png; http://en.wikipedia.org/wiki/
Image:Heatmap.png; http://en.wikipedia.org/wiki/Image:Microarray2.gif;
http://zellig.cpmc.columbia.edu/medlee/demo/; htp://www.plosone.org/article/fetchArticle.action?articleURI=info:doi/10.1371/journal.pone.0000441
14. Researchers have a choice
PAST MEDICAL HISTORY:
Past medical history showed she had
superficial phlebitis times two in the past, had
non-insulin dependent diabetes mellitus for
four years.
She had been hypothyroid for three years.
HISTORY OF PRESENT ILLNESS:
The patient is a 58-year-old female, …
http://upload.wikimedia.org/wikipedia/commons/7/76/PeptideMSMS.jpg; http://en.wikipedia.org/wiki/Image:Helices.png; http://en.wikipedia.org/wiki/
Image:Heatmap.png; http://en.wikipedia.org/wiki/Image:Microarray2.gif;
http://zellig.cpmc.columbia.edu/medlee/demo/; htp://www.plosone.org/article/fetchArticle.action?articleURI=info:doi/10.1371/journal.pone.0000441
15. Researchers have a choice
PAST MEDICAL HISTORY:
Past medical history showed she had
superficial phlebitis times two in the past, had
non-insulin dependent diabetes mellitus for
four years.
She had been hypothyroid for three years.
HISTORY OF PRESENT ILLNESS:
The patient is a 58-year-old female, …
http://upload.wikimedia.org/wikipedia/commons/7/76/PeptideMSMS.jpg; http://en.wikipedia.org/wiki/Image:Helices.png; http://en.wikipedia.org/wiki/
Image:Heatmap.png; http://en.wikipedia.org/wiki/Image:Microarray2.gif;
http://zellig.cpmc.columbia.edu/medlee/demo/; htp://www.plosone.org/article/fetchArticle.action?articleURI=info:doi/10.1371/journal.pone.0000441
16. Researchers have a choice
PAST MEDICAL HISTORY:
Past medical history showed she had
superficial phlebitis times two in the past, had
non-insulin dependent diabetes mellitus for
four years.
She had been hypothyroid for three years.
HISTORY OF PRESENT ILLNESS:
The patient is a 58-year-old female, …
http://upload.wikimedia.org/wikipedia/commons/7/76/PeptideMSMS.jpg; http://en.wikipedia.org/wiki/Image:Helices.png; http://en.wikipedia.org/wiki/
Image:Heatmap.png; http://en.wikipedia.org/wiki/Image:Microarray2.gif;
http://zellig.cpmc.columbia.edu/medlee/demo/; htp://www.plosone.org/article/fetchArticle.action?articleURI=info:doi/10.1371/journal.pone.0000441
18. But... costly for authors
Find
Organize
Document
Deidentify
Format
Decide
Ask
Submit
Answer questions
Worry about mistakes being found
Worry about data being misinterpreted
Worry about being scooped
Forgo money and IP and prestige???
21. ... on initiatives, requests,
requirements, and tools
• Funder requirements
• Journal requirements
• Public databases
• Data sharing grids
• Data formatting standards
• Peer encouragement in editorials, letters to the
editor...
22. Does it work?
http://www.flickr.com/photos/archeon/2941655917/
27. Who to share data with?
• everyone on the internet
• “qualified” researchers for
“qualified” research projects
• friends
• your lab
28. What data is shared?
• everything
• all the datapoints
• all the research notes
• code
• just what is needed to reproduce
the results in the paper
• raw? cleaned?
every processing step?
29. When is the data shared?
• upon collection
• upon submission for publication
• upon publication
• time-embargo after publication
• upon retirement or death
30. Where is it deposited?
• centralized datatype specific
repositories
• journal supplementary information
• institutional repositories
• disciplinary repositories
32. How to share it?
• massive datasets
• syntactic format
• semantic format
• sensitive data (privacy, endangered
species locations, security-
related, ...)
• what license or community norm
35. • biomedical data
• few privacy concerns raw data
(not images or processed)
• openly on the internet
• upon publication
• datasets are large but manageable
• datatypes with mature standards for
semantics, syntax, locations
http://www.flickr.com/photos/paulhami/1020538523//
36. but how much isn’t
shared?
what isn’t shared?
who isn’t sharing it?
why not?
how much does it matter?
what can we do
about it?
37. but how much isn’t
shared?
what isn’t shared?
who isn’t sharing it?
why not?
how much does it matter?
what can we do
about it?
38. Data sharing frequency depends
on how you ask
10%
25-40%
Campbell et al. JAMA. 2002.
Kyzas et al. J Natl Cancer Inst. 2005.
Vogeli et al. Acad Med. 2006.
Reidpath et al. Bioethics 2001.
39. Data sharing frequency depends
on datatype
DNA sequences
gene expression microarrays
proteomics spectra
0% 25% 50% 75% 100%
Noor et al. PLoS Biology 2006.
Ochsner et al. Nature Methods 2008.
Piwowar et al. PLoS ONE 2007.
Editorial. Nature Biotech 2007.
43. but how much isn’t
shared?
what isn’t shared?
who isn’t sharing it?
why not?
how much does it matter?
what can we do
about it?
44. http://en.wikipedia.org/wiki/DNA_microarray
http://en.wikipedia.org/wiki/Image:Heatmap.png
http://commons.wikimedia.org/wiki/
File:DNA_double_helix_vertikal.PNG
microarray
data
45. Funder Journal Investigator Institution Study
How often was
research data shared upon
publication?
46. How often was
research data shared upon
publication?
Number of studies that share their data
= _____________________________________
Number of studies that create data
47. How often was
research data shared upon
publication?
Number of studies that share their data
= _____________________________________
Number of studies that create data
49. Look for wetlab methods in full text:
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1522022&tool=pmcentrez
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1590031&tool=pmcentrez
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1482311&tool=pmcentrez#id331936
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=2082469&tool=pmcentrez
http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=126870&tool=pmcentrez#id442745
50. Query the full text of published articles:
("gene expression" AND microarray AND cell AND rna)
AND (rneasy OR trizol OR "real-time pcr")
NOT (“tissue microarray*” OR “cpg island*”)
51. How often was
research data shared upon
publication?
Number of studies that share their data
= _____________________________________
Number of studies that create data
54. How often was
research data shared upon
publication?
Number of studies that share their data
= _____________________________________
Number of studies that create data
55. results
11,603 studies that create data
we found shared datasets for 25%
58. Funder Journal Investigator Institution Study
funded by impact years since sector humans?
NIH? factor first paper
size mice?
size of strength of # pubs
grant policy impact plants?
# citations rank
sharing open cancer?
plan req’d? access? previously country
shared? clinical
funded by number of trial?
non-NIH? microarray previously
reused? number of
studies authors
published gender
year
60. author “experience”
Author publication history:
Author name Author-ity web service
Torvik & Smalheiser. (2009). Author Name
disambiguation: Disambiguation in MEDLINE. ACM Transactions on
Knowledge Discovery from Data, 3(3):11.
Citation counts:
64. funder mandates
Requires a data sharing plan
for studies funded after October 2003
that receive more than $500 000 in
direct funding per year
65. journal mandates
“An inherent principle of publication is that
others should be able to replicate and build
upon the authors' published claims.
Therefore, a condition of publication
in a Nature journal is that authors are
required to make materials, data and
associated protocols available in a publicly
accessible database …”
http://www.nature.com/authors/editorial_policies/availability.html
http://www.nature.com/nature/journal/v453/n7197/index.html
68. Proportion of datasets shared
0.0
0.2
0.4
0.6
0.8
1.0
Physiol Genomics
PLoS Genet
Genome Biol
Microbiology
PLoS One
BMC Genomics
Plant Cell
Genome Res
Eukaryot Cell
Appl Environ Microbiol
BMC Med Genomics
Hum Mol Genet
Proc Natl Acad Sci U S A
Infect Immun
Am J Respir Cell Mol Biol
Dev Biol
J Bacteriol
Mol Endocrinol
BMC Cancer
Plant Physiol
Biol Reprod
Blood
J Immunol
FASEB J
Toxicol Sci
J Exp Bot
Nucleic Acids Res
Diabetes
Mol Cell Biol
Mol Cancer Ther
BMC Bioinformatics
Stem Cells
FEBS Lett
J Neurosci
Am J Pathol
J Biol Chem
J Virol
OTHER
Cancer Res
J Clin Endocrinol Metab
Plant Mol Biol
Clin Cancer Res
Genomics
Journals
Invest Ophthalmol Vis Sci
Mol Hum Reprod
Carcinogenesis
Gene
Endocrinology
Oncogene
Cancer Lett
Biochem Biophys Res Commun
69. Proportion of datasets shared
0.0
0.2
0.4
0.6
0.8
1.0
Stanford University
University of Pennsylvania
University of Illinois
University of California, Los Angeles
University of Wisconsin, Madison
University of Washington
University of California, Davis
The University of British Columbia
University of California, San Francisco
University of Florida
University of California, San Diego
University of Minnesota, Twin Cities
Baylor College of Medicine
OTHER
Max Planck Gesellschaft
Harvard University
Duke University Medical Center
Yale University
Johns Hopkins University
University of Pittsburgh
Washington University in Saint Louis
University of Toronto
University of California, Berkeley
University of Michigan, Ann Arbor
Michigan State University
Institutions
National Cancer Institute
Tokyo Daigaku
70. Proportion of datasets shared
0.0
0.2
0.4
0.6
0.8
1.0
Stanford University
University of Pennsylvania
University of Illinois
University of California, Los Angeles
University of Wisconsin, Madison
University of Washington
University of California, Davis
The University of British Columbia
University of California, San Francisco
University of Florida
University of California, San Diego
University of Minnesota, Twin Cities
Baylor College of Medicine
OTHER
Max Planck Gesellschaft
Harvard University
Duke University Medical Center
Yale University
Johns Hopkins University
University of Pittsburgh
Washington University in Saint Louis
University of Toronto
University of California, Berkeley
University of Michigan, Ann Arbor
Michigan State University
Institutions
National Cancer Institute
Tokyo Daigaku
72. Multivariate nonlinear regressions with interactions
Odds Ratio
0.25 0.50 1.00 2.00 4.00 8.00
Has journal policy
Multivariate nonlinear regressions with interactions
Count of R01 & other NIH grants Odds Ratio
0.95
0.25 0.50 1.00 2.00 4.00 8.00
Authors prev GEOAE sharing & OA & microarray creation
Has journal policy
NO K funding other P funding
Count of R01 & or NIH grants
0.95
Authors prev GEOAE sharing & OA & microarray creation
NO K Journalfunding
funding or P impact
Institution high citations & collaboration
Journal policy consequences & Journal impact long halflife
Journal policy consequences & long halflife
Institution high citations NOTcollaboration & animals or mice
Instititution is government & NOT higher ed
NOT animals or mice
Last author num prev pubs & first year pub
Large NIH grant
Instititution is government & NOT higher ed Humans & cancer
NO geo reuse + YES high institution output
Last author num prev pubs & first year pub
First author num prev pubs & first year pub
Large NIH grant
Humans & cancer
NO geo reuse + YES high institution output
First author num prev pubs & first year pub
73. Odds Ratio
0.25 0.50 1.00 2.00 4.00
OA journal & previous GEO-AE sharing
Amount of NIH funding
0.95
Journal impact factor and policy
Higher Ed in USA
Cancer & humans
74. • association not causation
• lots of assumptions
• don’t know how generalizable it is
• hypothesis-generating
http://www.flickr.com/photos/vlastula/300102949/
75. what isn’t shared?
who isn’t sharing it?
• those studying cancer
• on human patient data
• in journals with few data sharing policies
(clincal journals)
• labs with fewer funding sources
• ...
76. (what is shared?
who is sharing it?)
• investigators who have shared before
• investigators who publish in open access journals
• from Stanford
• in Physiological Genomics
• ...
77. Take home
• current data repositories are not representative
of all data generated
• they are missing some of the good stuff
• Good news: actionable to learn from the leaders
and focus on the laggards
78. but how much isn’t
shared?
what isn’t shared?
who isn’t sharing it?
why not?
how much does it matter?
what can we do
about it?
81. Withhold because too much effort,
desire for continued publishing
sharing is too much effort
want student or jr faculty to publish more
they themselves want to publish more
cost
industrial sponsor
confidentiality
commercial value of results
0% 20% 40% 60% 80%
Campbell et al. JAMA 2002.
83. but how much isn’t
shared?
what isn’t shared?
who isn’t sharing it?
why not?
how much does it matter?
what can we do
about it?
84. Estimating societal benefit
‐ assume each database hit saves $0.10, or a
fraction of data collection costs
‐ assume the value is approximated by the
(idealized) funding target for data
maintenance:
20‐25% the cost of generating the data
Remembering, moreover, the indirect benefits are much
higher than the direct ones.
Ball et al. Nature Biotechol. 2004.
85. Number of stakeholders
Foster et al. Share and share alike: deciding how to distribute the scientific and social benefits of genomic data.
Nature Reviews Genetics 8, 633-639
86. Impact on training
Survey of doctoral students and postdocs:
23.0% been denied access to information, data,
materials, or programming associated with published
research
28-50% reported withholding caused negative effects on
these aspects of their training:
•progress of their research,
•rate of discovery in their lab/research group,
•quality of their relationships with academic scientists,
•quality of their education,
•level of communication in their lab/research group.
Vogeli et al. Acad Med. 2006 Feb; 81(2):128-36
93. What would make it easier? help
and straightforward guidelines
more funder time and money
help with confidentiality issues
on-site help
more training
better guidelines
better tools
simpler requirements
less staff turn-over
0% 25% 50% 75%
Hedstrom et al. IASSIST 2006.
94. What would make it easier? help
and straightforward guidelines
more funder time and money
help with confidentiality issues
on-site help
more training
better guidelines
better tools
simpler requirements
less staff turn-over
0% 25% 50% 75%
Hedstrom et al. IASSIST 2006.
95. What would make it easier? help
and straightforward guidelines
more funder time and money
help with confidentiality issues
on-site help
more training
better guidelines
better tools
simpler requirements
less staff turn-over
0% 25% 50% 75%
Hedstrom et al. IASSIST 2006.
100. NSF-funded distributed framework
and cyberinfrastructure for
environmental science.
Dryad is a repository of data
underlying scientific publications,
with an initial focus on evolution,
ecology, and related fields.
The National Evolutionary
Synthesis Center, NSF-funded:
• Duke University,
• UNC at Chapel Hill
• North Carolina State University
103. who reuses data?
why?
when?
who doesn’t?
which datasets are most likely to be
reused?
how many datasets could be reused but
aren’t?
why aren’t they?
what can we do about it?
what should we do about it?
104. I share my code and data at http://www.researchremix.org
Sharing data is not easy.
Some is better than none.
Be the change you want to see.
http://www.flickr.com/photos/myklroventine/892446624/
105. Dept of Biomedical Informatics at U of Pittsburgh
NLM for training grant funding
Open science online community and those who release their
articles, datasets and photos openly
NEDCC
thank you
109. Benefits both societal and personal
saves other people effort
for the public good
will be cited and enhance my reputation
saves me effort in answering questions
saves me effort in managing my data
0% 20% 40% 60% 80%
Hedstrom et al. IASSIST 2006.