Marker assisted selection( mas) and its application in plant breedingHemantkumar Sonawane
Marker Types,Prerequisites for efficient marker-assisted breeding programmes,Advantages of MAS,Limitations of MAS ,Marker Assisted Breeding Schemes,• 1. Marker- assisted backcrossing,2. Marker- Assisted evaluation of breeding material,3 Gene pyramiding,4. Early generation selection ,Combined approaches,MAB: I level of Selection – FOREGROUND SELECTION,Second level of selection: Recombinant Selection,MAB: III Level of Selection BACKGROUND SELECTION,
Marker assisted selection( mas) and its application in plant breedingHemantkumar Sonawane
Marker Types,Prerequisites for efficient marker-assisted breeding programmes,Advantages of MAS,Limitations of MAS ,Marker Assisted Breeding Schemes,• 1. Marker- assisted backcrossing,2. Marker- Assisted evaluation of breeding material,3 Gene pyramiding,4. Early generation selection ,Combined approaches,MAB: I level of Selection – FOREGROUND SELECTION,Second level of selection: Recombinant Selection,MAB: III Level of Selection BACKGROUND SELECTION,
microRNA in Plant Defence and Pathogen Counter-defenceMahtab Rashid
The presentation is about the role of microRNA in plant defence and the pathogen counter-defences which they adopt to escape or evade the plant defence mechanism.
This slide will help you understand the basics of CRISPR-Cas9, Mechanism, Application, Advantages, and Disadvantages of CRISPR-Cas9, Future Concerns, Future Possibilities.
Ethical issues related to animal biotechnologyKAUSHAL SAHU
Introduction
Why are genetically modified animals produced?
Examples of transgenic animals
Why are animals used instead of genetically modified microbes or plants?
Ethical issues
Religious concerns
Responsibility of Scientists
Need for Guidelines
Conclusion
References
The problems of post retraction citation - and mitigation strategies that wor...jodischneider
Presentation for the Bibliometrics & Research Assessment Symposium 2020 (bibSymp20) https://www.nihlibrary.nih.gov/services/bibliometrics/bibSymp20
October 9, 2020
Retraction is intended to remove articles from the citable literature. However, a series of studies from over 30 years, from 1990 through 2020, have found that many retracted papers continue to be cited, and cited positively, even following misconduct-related retractions. For instance, a fraudulent clinical trial report retracted in 2008 continues to receive citations in 2020, and 96% of post-retraction citations do not mention its citation - perhaps because its retraction not marked on the publisher website and its retraction notice cannot be readily retrieved from 7 out of 8 databases (8 out of 9 database records) we tested. This talk draws an ongoing systematic mapping study of research about retraction and our own research projects to summarize what is known about post-retraction citation in biomedicine. We outline practical steps that authors and reviewers can take to avoid being caught out by poorly marked retracted papers.
20 minutes including Q&A
A Big Data Application Model To Track CoronaVirus Infected Patients �KayMak
Social Network Analysis https://youtu.be/H_nM6LuCH50
How CoronaVirus Spread in China Time Series https://youtu.be/7zqjshClu90
Dashboard: Map Track the spread of Coronavirus https://youtu.be/sR2OTL7JZTk
Corona Virus Global Infection Spread https://youtu.be/avsqTXgayjo
Informatics for Disease Surveillance – New TechnologiesDr Wasim Ahmed
A guest lecture on informatics for disease surveillance, looking at a number of new new technologies. Delivered at the School of Health and Related Research.
Presentation at "Strategies for managing social media research data", Feb 12, 2016. Cambridge. http://www.data.cam.ac.uk/events/strategies-managing-social-media-research-data
This presentation was provided by Alberto Pepe of Authorea, during the NISO hot topic event "Preprints." The virtual conference was held on April 21, 2021.
Social Media and Medicine: Relevance to Cancer CareMatthew Katz
Social media are pervasive, powerful communications tools. What are the risks and benefits of using them in cancer care? I discuss it in this talk at Yale April 10, 2014.
microRNA in Plant Defence and Pathogen Counter-defenceMahtab Rashid
The presentation is about the role of microRNA in plant defence and the pathogen counter-defences which they adopt to escape or evade the plant defence mechanism.
This slide will help you understand the basics of CRISPR-Cas9, Mechanism, Application, Advantages, and Disadvantages of CRISPR-Cas9, Future Concerns, Future Possibilities.
Ethical issues related to animal biotechnologyKAUSHAL SAHU
Introduction
Why are genetically modified animals produced?
Examples of transgenic animals
Why are animals used instead of genetically modified microbes or plants?
Ethical issues
Religious concerns
Responsibility of Scientists
Need for Guidelines
Conclusion
References
The problems of post retraction citation - and mitigation strategies that wor...jodischneider
Presentation for the Bibliometrics & Research Assessment Symposium 2020 (bibSymp20) https://www.nihlibrary.nih.gov/services/bibliometrics/bibSymp20
October 9, 2020
Retraction is intended to remove articles from the citable literature. However, a series of studies from over 30 years, from 1990 through 2020, have found that many retracted papers continue to be cited, and cited positively, even following misconduct-related retractions. For instance, a fraudulent clinical trial report retracted in 2008 continues to receive citations in 2020, and 96% of post-retraction citations do not mention its citation - perhaps because its retraction not marked on the publisher website and its retraction notice cannot be readily retrieved from 7 out of 8 databases (8 out of 9 database records) we tested. This talk draws an ongoing systematic mapping study of research about retraction and our own research projects to summarize what is known about post-retraction citation in biomedicine. We outline practical steps that authors and reviewers can take to avoid being caught out by poorly marked retracted papers.
20 minutes including Q&A
A Big Data Application Model To Track CoronaVirus Infected Patients �KayMak
Social Network Analysis https://youtu.be/H_nM6LuCH50
How CoronaVirus Spread in China Time Series https://youtu.be/7zqjshClu90
Dashboard: Map Track the spread of Coronavirus https://youtu.be/sR2OTL7JZTk
Corona Virus Global Infection Spread https://youtu.be/avsqTXgayjo
Informatics for Disease Surveillance – New TechnologiesDr Wasim Ahmed
A guest lecture on informatics for disease surveillance, looking at a number of new new technologies. Delivered at the School of Health and Related Research.
Presentation at "Strategies for managing social media research data", Feb 12, 2016. Cambridge. http://www.data.cam.ac.uk/events/strategies-managing-social-media-research-data
This presentation was provided by Alberto Pepe of Authorea, during the NISO hot topic event "Preprints." The virtual conference was held on April 21, 2021.
Social Media and Medicine: Relevance to Cancer CareMatthew Katz
Social media are pervasive, powerful communications tools. What are the risks and benefits of using them in cancer care? I discuss it in this talk at Yale April 10, 2014.
Digital communications are changing how we share health information. Are social media compatible with academic medicine and oncology?
This is a talk given at Brigham & Women's Hospital to the Harvard Radiation Oncology Program residents and staff on December 19 2014. It is intended as a survey rather than definitive presentation, highlighting the need for more research.
Tweet Your Pubs: How Altmetrics are Changing the Way We Measure Research ImpactRobin Featherstone
Presentation given to the Northern Alberta Health Libraries Association (NAHLA) Trends Mini Conference in Edmonton at the University of Alberta on May 2, 2014
The Transformational Power - and Promise - of Social MediaMayo Clinic
Presentation at Transform 11 (#txfm11) by Lee Aase, ePatient Dave deBronkart and Dr. Bryan Vartabedian on the power and promise of social media in health care.
Presentation at the Philippine National Health Research Week preconference meeting: Rallying Communicators for Science, Technology, and Innovation in Health | Society of Health Research Communicators (SHARE). 22 August 2017, Hotel Jen, Manila.
Invited presentation at Presenting Data: How to Convey Information Most Effectively Seminar, Centre of Research Excellence in Patient Safety, School of Public Health and Preventive Medicine, Monash University, February 2015.
Continued citation of bad science and what we can do about it--2021-02-19jodischneider
Title: Continued Citation of Bad Science and What We Can Do About It
Abstract: Even papers that falsify data continue to be cited. I describe network and text analysis for studying how authors continue to cite bad science: articles retracted from the literature due to serious flaws or errors. Jodi will present an in-depth case study of a human trial cited for over 10 years after it was retracted for falsifying data. Then, will describe how the team scaled up to study a data set of 7000 retracted papers and hundreds of thousands of citations. Finally, Jodi will discuss an ongoing Sloan-funded stakeholder consultation that is bringing editors, publishers, librarians, researchers, and research integrity experts together to address this problem.
Similar to The Dark Side of Science: Misconduct in Biomedical Research (20)
AI en IP (Artificieele Intelligentie en Intellectueel Eigendom)voginip
Lezing door Fulco Blokhuis over de juridische aspecten die optreden bij generatieve AI, zoals ChatGPT, Dall-e e.d.
VOGIN-IP-lezing 28 april 2024 Amsterdam
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Slide 1: Title Slide
Extrachromosomal Inheritance
Slide 2: Introduction to Extrachromosomal Inheritance
Definition: Extrachromosomal inheritance refers to the transmission of genetic material that is not found within the nucleus.
Key Components: Involves genes located in mitochondria, chloroplasts, and plasmids.
Slide 3: Mitochondrial Inheritance
Mitochondria: Organelles responsible for energy production.
Mitochondrial DNA (mtDNA): Circular DNA molecule found in mitochondria.
Inheritance Pattern: Maternally inherited, meaning it is passed from mothers to all their offspring.
Diseases: Examples include Leber’s hereditary optic neuropathy (LHON) and mitochondrial myopathy.
Slide 4: Chloroplast Inheritance
Chloroplasts: Organelles responsible for photosynthesis in plants.
Chloroplast DNA (cpDNA): Circular DNA molecule found in chloroplasts.
Inheritance Pattern: Often maternally inherited in most plants, but can vary in some species.
Examples: Variegation in plants, where leaf color patterns are determined by chloroplast DNA.
Slide 5: Plasmid Inheritance
Plasmids: Small, circular DNA molecules found in bacteria and some eukaryotes.
Features: Can carry antibiotic resistance genes and can be transferred between cells through processes like conjugation.
Significance: Important in biotechnology for gene cloning and genetic engineering.
Slide 6: Mechanisms of Extrachromosomal Inheritance
Non-Mendelian Patterns: Do not follow Mendel’s laws of inheritance.
Cytoplasmic Segregation: During cell division, organelles like mitochondria and chloroplasts are randomly distributed to daughter cells.
Heteroplasmy: Presence of more than one type of organellar genome within a cell, leading to variation in expression.
Slide 7: Examples of Extrachromosomal Inheritance
Four O’clock Plant (Mirabilis jalapa): Shows variegated leaves due to different cpDNA in leaf cells.
Petite Mutants in Yeast: Result from mutations in mitochondrial DNA affecting respiration.
Slide 8: Importance of Extrachromosomal Inheritance
Evolution: Provides insight into the evolution of eukaryotic cells.
Medicine: Understanding mitochondrial inheritance helps in diagnosing and treating mitochondrial diseases.
Agriculture: Chloroplast inheritance can be used in plant breeding and genetic modification.
Slide 9: Recent Research and Advances
Gene Editing: Techniques like CRISPR-Cas9 are being used to edit mitochondrial and chloroplast DNA.
Therapies: Development of mitochondrial replacement therapy (MRT) for preventing mitochondrial diseases.
Slide 10: Conclusion
Summary: Extrachromosomal inheritance involves the transmission of genetic material outside the nucleus and plays a crucial role in genetics, medicine, and biotechnology.
Future Directions: Continued research and technological advancements hold promise for new treatments and applications.
Slide 11: Questions and Discussion
Invite Audience: Open the floor for any questions or further discussion on the topic.
The increased availability of biomedical data, particularly in the public domain, offers the opportunity to better understand human health and to develop effective therapeutics for a wide range of unmet medical needs. However, data scientists remain stymied by the fact that data remain hard to find and to productively reuse because data and their metadata i) are wholly inaccessible, ii) are in non-standard or incompatible representations, iii) do not conform to community standards, and iv) have unclear or highly restricted terms and conditions that preclude legitimate reuse. These limitations require a rethink on data can be made machine and AI-ready - the key motivation behind the FAIR Guiding Principles. Concurrently, while recent efforts have explored the use of deep learning to fuse disparate data into predictive models for a wide range of biomedical applications, these models often fail even when the correct answer is already known, and fail to explain individual predictions in terms that data scientists can appreciate. These limitations suggest that new methods to produce practical artificial intelligence are still needed.
In this talk, I will discuss our work in (1) building an integrative knowledge infrastructure to prepare FAIR and "AI-ready" data and services along with (2) neurosymbolic AI methods to improve the quality of predictions and to generate plausible explanations. Attention is given to standards, platforms, and methods to wrangle knowledge into simple, but effective semantic and latent representations, and to make these available into standards-compliant and discoverable interfaces that can be used in model building, validation, and explanation. Our work, and those of others in the field, creates a baseline for building trustworthy and easy to deploy AI models in biomedicine.
Bio
Dr. Michel Dumontier is the Distinguished Professor of Data Science at Maastricht University, founder and executive director of the Institute of Data Science, and co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles. His research explores socio-technological approaches for responsible discovery science, which includes collaborative multi-modal knowledge graphs, privacy-preserving distributed data mining, and AI methods for drug discovery and personalized medicine. His work is supported through the Dutch National Research Agenda, the Netherlands Organisation for Scientific Research, Horizon Europe, the European Open Science Cloud, the US National Institutes of Health, and a Marie-Curie Innovative Training Network. He is the editor-in-chief for the journal Data Science and is internationally recognized for his contributions in bioinformatics, biomedical informatics, and semantic technologies including ontologies and linked data.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
2. Publications are the foundation of science
• Science is about finding the truth
• Science builds upon science: Publications as building blocks
• Scientists build upon each other's work
• Built on trust, but science is not immune to fraud
2
www.piqsels.com Ivan Radic, www.Flickr.com
3. What is Science Misconduct?
3
Source: https://www.a-stw.com/
Plagiarism
Copying texts or
ideas without
giving credit
Fabrication
Making up results
No measurements
Falsification
Changing
measurements to
fit hypothesis
Leaving out outliers
Questionable Research
Practices (QRP)
Not publishing negative results
Not citing relevant papers
Statistical flaws
Incomplete reporting
Science Misconduct
4. Behind each misconduct case is a sad story
4
• Why do scientists commit fraud?
• Which author is responsible?
• All authors will be damaged
• Paper concerns vs. who did it
5. It all started with a plagiarism check
• iThenticate, TurnItIn, WriteCheck
• Google / Scholar: 5-10 words between quotes
• Personal project (2013):
• 80 review/research papers found, reported to journals
• 35 retracted, 11 corrected, 34 not addressed
5
10. Type I: Simple Duplication
10
Estradiol inhibits vascular endothelial cells pro-inflammatory activation
Montreal Heart Institute, Canada
Molecular and Cellular Biochemistry (2013) , DOI: 10.1007/s11010-012-1482-9
Reported to journal: October 2015. No action yet.
11. Type I: Simple Duplication
11
Estradiol inhibits vascular endothelial cells pro-inflammatory activation
Montreal Heart Institute, Canada
Molecular and Cellular Biochemistry (2013) , DOI: 10.1007/s11010-012-1482-9
Reported to journal: October 2015. No action yet.
12. Type II: Duplication with repositioning
12
First Affiliated Hospital of Harbin Medical University, China
PLOS ONE (2014), DOI: 10.1371/journal.pone.0091566
Reported Oct 2015, retracted March 2019, cited by 27
13. Type II: Duplication with repositioning
13
First Affiliated Hospital of Harbin Medical University, China
PLOS ONE (2014), DOI: 10.1371/journal.pone.0091566
Reported Oct 2015, retracted March 2019, cited by 27
14. Type III: Duplication with alteration
14
DOI: 10.1016/j.jsps.2015.02.021, reported online August 2019, cited 31 times
15. Type III: Duplication with alteration
15
DOI: 10.1016/j.jsps.2015.02.021, reported online August 2019, cited 31 times
16. Type III: Duplication with alteration
16
Université de la Mediterranée, Marseille, France
Journal of Infectious Diseases (2003), DOI: 10.1086/379080, cited by 116 papers
Reported online March 2021, not addressed yet.
17. Type III: Duplication with alteration
17
Université de la Mediterranée, Marseille, France
Journal of Infectious Diseases (2003), DOI: 10.1086/379080, cited by 116 papers
Reported online March 2021, not addressed yet.
18. Type III: Duplication with alteration
18
Hubrecht Laboratory (NIOB-KNAW), The Netherlands
Science (2007), DOI: 10.1126/science.1136699, cited 342 times
Reported to journal April 2015, retracted November 2020
19. Type III: Duplication with alteration
19
Hubrecht Laboratory (NIOB-KNAW), The Netherlands
Science (2007), DOI: 10.1126/science.1136699, cited 342 times
Reported to journal April 2015, retracted November 2020
20. Type III: Duplication with Alteration
20
PBS Ps-
AFP1
2h
6h
Indian Institute of Technology Kharagpur, India
Biochimie (2013), DOI: 10.1016/j.biochi.2013.06.027, cited by 25
Reported online, March 2016. Corrected July 2016.
21. Type III: Duplication with alteration
21
Enhanced photocatalytic degradation of 4-chlorophenol by Zr4+ doped nano TiO2
Anna University, India, cited 179 times.
Journal of Molecular Catalysis A (2007), DOI: 10.1016/j.molcata.2006.10.051
Reported to journal editors in September 2019; Retracted July 2022
22. Type III Duplication: NMR spectrum
22
Scientific Reports (2020), DOI: 10.1038/s41598-020-68709-5
Reported August 2020, retracted March 2021
23. Inappropriate image duplication
• I scanned 20,621 papers from 1995-2014 - by eye
• 40 journals from 14 publishers
• Found ~ 800 papers with duplicated figures (4%)
• 3 types: Simple - Repositioned - Altered
• Not all are misconduct! About half intentional: 2%
• Alteration in other data types much harder to detect
23
24. Journals are very slow to respond
24
2014/2015: 782 papers reported to journals
65% of papers have not been corrected/retracted five years after reporting
March 2023: 6,907 papers found; 2,800 reported to journals/institutions
25. Reporting concerns about research misconduct
25
The Official Professional Way:
● Contact Editor-in-Chief of journal
● Contact Research Integrity Officer of university
● Investigation might follow - or not
The Experienced, Frustrated, and Proactive Way
● Posting on PubPeer.com (6,419 of 6,907)
PubPeer.com
28. Artificial intelligence can create fake papers
28
Futurism
Tiffany Hsu and Stuart A. Thompson, February 2023
29. Paper Mills sell authorships or fake papers
• Scientific paper mills
• Sell authorships on already accepted papers
• Sell fake papers written by ghostwriters with fabricated data
• Credit: Anna Abalkina, Jana Christopher, Jennifer Byrne, Smut Clyde, Morty,
Tiger, Cheshire
29
31. Tadpole Paper Mill: same blot background
31
● ~600 papers found so far
● Same blot background across all papers
● Bands generated through Generative Adversarial Networks (GAN)?
DOI: 10.1002/ptr.6336
32. Science Misconduct - Discussion
• Science is about discovering the truth
• Role of AI in detecting or generating science fraud?
• Focus less on publications / productivity
• More reproducibility studies
• If you see something, say something RI Officer, Journal EiC, PubPeer.com
• It takes a village: role of reviewers, journals, institutions
• Tremendous cost of science misconduct (scientists, science)
32