This document summarizes a presentation on developing a heuristic method to detect sleep patterns from wrist-worn accelerometer data in the UK Biobank study. The method defines periods of sustained inactivity as potential sleep episodes. Genetic analysis of these sleep measures identified 47 genetic loci associated with sleep. Mendelian randomization analysis found insomnia increased risk of heart disease, and being an "early bird" reduced risk of schizophrenia and depression. The work highlights the importance of open source software and data sharing for advancing physical behavior research.
Exploring ICP, Tissue Oxygenation and RSNA with Implantable TelemetryInsideScientific
This webinar offers insight into unique applications of Millar implantable telemetry, including the measurement of intra-cranial pressure (ICP), concurrent sympathetic nerve activity (SNA) and arterial pressure recordings, and tissue oxygen.
Experts share experimental methods and highlight distinctive capabilities of this technology that have helped each of them uncover scientific findings in the areas of renal sympathetic nerve activity (RSNA) and cerebral perfusion in rats, respectively.
Dr. Fiona McBryde discusses her recent experience working with rats where she has successfully instrumented subjects with two telemeters, permitting continuous recording of arterial blood pressure, intracranial pressure and brain oxygenation. Importantly, she shares tips and prescribed best-practices for both single and dual telemeter implantation, and discusses experimental design for more complex multi-parameter research studies.
Professor Jacqueline Phillips discusses highlights from her recent publication, “Direct conscious telemetry recordings demonstrate increased renal sympathetic nerve activity (RSNA) in rats with chronic kidney disease”, specifically focusing on HOW scientists can successfully acquire continuous RSNA data and should approach data analysis.
The Science of Sweet Dreams: Predicting Sleep Efficiency from Wearable Devic...Luis Fernandez Luque
Lack of sleep can erode mental and physical well-being, often exacerbating health problems such as obesity. Wearable devices that capture and analyze sleep quality through predictive methodologies can help patients and medical practitioners make behavioral health decisions that can lead to better sleep and improved health.
http://doi.ieeecomputersociety.org/10.1109/MC.2017.91
Amit Sheth, Pramod Anantharam, Krishnaprasad Thirunarayan, "kHealth: Proactive Personalized Actionable Information for Better Healthcare", Workshop on Personal Data Analytics in the Internet of Things at VLDB2014, Hangzhou, China, September 5, 2014.
Accompanying Video: http://youtu.be/pqcbwGYHPuc
Paper: http://www.knoesis.org/library/resource.php?id=2008
Exploring ICP, Tissue Oxygenation and RSNA with Implantable TelemetryInsideScientific
This webinar offers insight into unique applications of Millar implantable telemetry, including the measurement of intra-cranial pressure (ICP), concurrent sympathetic nerve activity (SNA) and arterial pressure recordings, and tissue oxygen.
Experts share experimental methods and highlight distinctive capabilities of this technology that have helped each of them uncover scientific findings in the areas of renal sympathetic nerve activity (RSNA) and cerebral perfusion in rats, respectively.
Dr. Fiona McBryde discusses her recent experience working with rats where she has successfully instrumented subjects with two telemeters, permitting continuous recording of arterial blood pressure, intracranial pressure and brain oxygenation. Importantly, she shares tips and prescribed best-practices for both single and dual telemeter implantation, and discusses experimental design for more complex multi-parameter research studies.
Professor Jacqueline Phillips discusses highlights from her recent publication, “Direct conscious telemetry recordings demonstrate increased renal sympathetic nerve activity (RSNA) in rats with chronic kidney disease”, specifically focusing on HOW scientists can successfully acquire continuous RSNA data and should approach data analysis.
The Science of Sweet Dreams: Predicting Sleep Efficiency from Wearable Devic...Luis Fernandez Luque
Lack of sleep can erode mental and physical well-being, often exacerbating health problems such as obesity. Wearable devices that capture and analyze sleep quality through predictive methodologies can help patients and medical practitioners make behavioral health decisions that can lead to better sleep and improved health.
http://doi.ieeecomputersociety.org/10.1109/MC.2017.91
Amit Sheth, Pramod Anantharam, Krishnaprasad Thirunarayan, "kHealth: Proactive Personalized Actionable Information for Better Healthcare", Workshop on Personal Data Analytics in the Internet of Things at VLDB2014, Hangzhou, China, September 5, 2014.
Accompanying Video: http://youtu.be/pqcbwGYHPuc
Paper: http://www.knoesis.org/library/resource.php?id=2008
Noninvasive, Automated Measurement of Sleep, Wake and Breathing in RodentsInsideScientific
In this exclusive webinar sponsored by Signal Solutions LLC, Dr. Bruce O’Hara discusses methodology, best-practices and use studies of the PiezoSleep system. Discussion focuses on how these techniques can answer questions about animal behavior, phenotyping and relationships between sleep and disease. Dr. O’Hara also highlights the benefits of the PiezoSleep system that can assess sleep, wake and breathing variables.
Large Language Models, No-Code, and Responsible AI - Trends in Applied NLP in...David Talby
An April 2023 presentation to the AMIA working group on natural language processing. The talk focuses on three current trends in NLP and how they apply in healthcare: Large language models, No-code, and Responsible AI.
ReComp and P4@NU: Reproducible Data Science for HealthPaolo Missier
brief overview of the ReComp project (http://recomp.org.uk) on Selective recurring re-computation of complex analytics, and a brief outlook for the P4@NU project on seeking digital biomarkers for age-0related metabolic diseases
We always prefer an unobtrusive continuous health monitoring system in the home for the purpose of assessing early health changes. Identification followed by assessment of the health issues at early stages of health disorder provides a window of opportunity for curing the issues before they become lethal. This presentation discusses various Artificial Intelligence techniques which can be used in this regard.
Presented at International Workshop on
Frontiers of Neuroengineering,
Brain-machine Interfaces
& Neural Prostheses
Zhejiang University, Hangzhou, China
March 29, 2011
Obtrusiveness of smartphone applications for sleep healthIJECEIAES
Unobtrusiveness is one of the main issues concerning health-related systems. Many developers affirm that their systems do not burden users; however, this is not always achieved. This article evaluates the obtrusiveness of various systems developed to improve sleep quality. The systems analyzed are related to sleep hygiene, since it has become an interesting topic for researchers, physicians and people in general, mainly because it has become part of the methods used to estimate a persons’ health status A set of design elements are presented as keys to achieving unobtrusiveness. We propose a scale to measure the level of unobtrusiveness and use it to evaluate several systems, with a focus on smartphone applications.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Digital Scientific Notations are expected to solve some of the problems we have in computational science today. In particular, they should make the verification of computational science by human scientists possible again. Leibniz is a Digital Scientific Notation for the physical sciences currently under development. This presentation gives an overview of the current state.
Case Studies in Home Cage Monitoring: Rodent Behavior, Circadian Biology and ...InsideScientific
Automated home cage behavioral monitoring is receiving increasing attention from the scientific community because of its benefits with regards to translational research, data replicability and animal welfare. In this webinar, Kenneth Dyar (Helmholtz Diabetes Center) and Joanna Moore (GSK) discuss how home cage monitoring can be used to reduce animal stress, optimize methodology and guide physiology and animal behavior research.
Dr. Kenneth Dyar
Passive locomotor activity monitoring for real-time circadian study design
Circadian clocks are fundamental determinants of physiology, behavior and health. For skeletal muscle, the circadian clock promotes insulin sensitivity and orchestrates rhythms of glucose, lipid, and amino acid metabolism. Physical activity synchronizes circadian clocks by altering body temperature and through distribution of various hormones and metabolites. Research suggests that misalignment of the ‘muscle clock’ plays an important pathophysiological role in metabolic disease. In this webinar, Dr. Kenneth Dyar highlights some examples of how the DVC system can be used for locomotor activity monitoring in order to evaluate circadian alignment before, during or after various dietary and pharmacological interventions.
Dr. Joanna Moore
Using home-cage monitoring to determine the impact of timed mating on male mouse welfare
The use of sterile male mice to induce pseudopregnancy in female mice assigned for the implantation of embryos is a vital component in the production of Genetically Altered Animals (GAA). This process involves swapping a genetically sterile male’s female companion for a new female. In this presentation, Dr. Joanna Moore discusses the use of home cage activity monitoring to evaluate the potential impact of this procedure on the welfare of male mice and how the impact of this intervention may be reduced. All animal studies were ethically reviewed and carried out in accordance with the Animals (Scientific Procedures) Act 1986 and the GSK Policy on the Care, Welfare and Treatment of Animals.
Key topics will include…
- Using home cage activity as a readout for animal welfare
- Using locomotor activity to optimize methodology and validate study design in real-time
- Pre-study screening of cohorts for outliers
Managing Health and Disease Using Omics and Big DataLaura Berry
Presented at the NGS Tech and Applications Congress: USA. To find out more, visit:
www.global-engage.com
Michael Snyder is a Professor, Chair of Genetics and Director of the Stanford Center for Genomics and Personalized Medicine at Stanford University. In this presentation Michael discusses using omics and big data to predict disease risk and catch early disease onset.
The Dog Collar project is a citizen science project encouraging pet owners to understand better their animal while contributing to research.
This is an open hardware collar containing motion sensors (3d gyroscope and accelerometers) to measure the activity of a dogs. An onboard memory and battery will allow data to be stored for days. A bluetooth module allow synchronisation with moibile devices and computers.
Dog owners will be able to know if their dog exercice enought and what he is doing along the day. As it is an open source projet dog owners are always owners of their data and can choose to share or not anonymized data with researchers. Those data are very usefull for research on aging as dog age in 20 in the same way as humans in 80 years. Moreover dog have a quite know genotype and so researchers will be able to correlate genotype phenotype and environemental factors on a large scale.
There is also an educational project aiming at childrens : the idea is to bring the children to be more curious about nature around. They learn new things about animals by observing their dog.
The Human Cell Atlas Data Coordination PlatformLaura Clarke
This presentation gives a brief summary of the Human Cell Atlas project and describes the data coordination platform which is being built to support it.
Noninvasive, Automated Measurement of Sleep, Wake and Breathing in RodentsInsideScientific
In this exclusive webinar sponsored by Signal Solutions LLC, Dr. Bruce O’Hara discusses methodology, best-practices and use studies of the PiezoSleep system. Discussion focuses on how these techniques can answer questions about animal behavior, phenotyping and relationships between sleep and disease. Dr. O’Hara also highlights the benefits of the PiezoSleep system that can assess sleep, wake and breathing variables.
Large Language Models, No-Code, and Responsible AI - Trends in Applied NLP in...David Talby
An April 2023 presentation to the AMIA working group on natural language processing. The talk focuses on three current trends in NLP and how they apply in healthcare: Large language models, No-code, and Responsible AI.
ReComp and P4@NU: Reproducible Data Science for HealthPaolo Missier
brief overview of the ReComp project (http://recomp.org.uk) on Selective recurring re-computation of complex analytics, and a brief outlook for the P4@NU project on seeking digital biomarkers for age-0related metabolic diseases
We always prefer an unobtrusive continuous health monitoring system in the home for the purpose of assessing early health changes. Identification followed by assessment of the health issues at early stages of health disorder provides a window of opportunity for curing the issues before they become lethal. This presentation discusses various Artificial Intelligence techniques which can be used in this regard.
Presented at International Workshop on
Frontiers of Neuroengineering,
Brain-machine Interfaces
& Neural Prostheses
Zhejiang University, Hangzhou, China
March 29, 2011
Obtrusiveness of smartphone applications for sleep healthIJECEIAES
Unobtrusiveness is one of the main issues concerning health-related systems. Many developers affirm that their systems do not burden users; however, this is not always achieved. This article evaluates the obtrusiveness of various systems developed to improve sleep quality. The systems analyzed are related to sleep hygiene, since it has become an interesting topic for researchers, physicians and people in general, mainly because it has become part of the methods used to estimate a persons’ health status A set of design elements are presented as keys to achieving unobtrusiveness. We propose a scale to measure the level of unobtrusiveness and use it to evaluate several systems, with a focus on smartphone applications.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Digital Scientific Notations are expected to solve some of the problems we have in computational science today. In particular, they should make the verification of computational science by human scientists possible again. Leibniz is a Digital Scientific Notation for the physical sciences currently under development. This presentation gives an overview of the current state.
Case Studies in Home Cage Monitoring: Rodent Behavior, Circadian Biology and ...InsideScientific
Automated home cage behavioral monitoring is receiving increasing attention from the scientific community because of its benefits with regards to translational research, data replicability and animal welfare. In this webinar, Kenneth Dyar (Helmholtz Diabetes Center) and Joanna Moore (GSK) discuss how home cage monitoring can be used to reduce animal stress, optimize methodology and guide physiology and animal behavior research.
Dr. Kenneth Dyar
Passive locomotor activity monitoring for real-time circadian study design
Circadian clocks are fundamental determinants of physiology, behavior and health. For skeletal muscle, the circadian clock promotes insulin sensitivity and orchestrates rhythms of glucose, lipid, and amino acid metabolism. Physical activity synchronizes circadian clocks by altering body temperature and through distribution of various hormones and metabolites. Research suggests that misalignment of the ‘muscle clock’ plays an important pathophysiological role in metabolic disease. In this webinar, Dr. Kenneth Dyar highlights some examples of how the DVC system can be used for locomotor activity monitoring in order to evaluate circadian alignment before, during or after various dietary and pharmacological interventions.
Dr. Joanna Moore
Using home-cage monitoring to determine the impact of timed mating on male mouse welfare
The use of sterile male mice to induce pseudopregnancy in female mice assigned for the implantation of embryos is a vital component in the production of Genetically Altered Animals (GAA). This process involves swapping a genetically sterile male’s female companion for a new female. In this presentation, Dr. Joanna Moore discusses the use of home cage activity monitoring to evaluate the potential impact of this procedure on the welfare of male mice and how the impact of this intervention may be reduced. All animal studies were ethically reviewed and carried out in accordance with the Animals (Scientific Procedures) Act 1986 and the GSK Policy on the Care, Welfare and Treatment of Animals.
Key topics will include…
- Using home cage activity as a readout for animal welfare
- Using locomotor activity to optimize methodology and validate study design in real-time
- Pre-study screening of cohorts for outliers
Managing Health and Disease Using Omics and Big DataLaura Berry
Presented at the NGS Tech and Applications Congress: USA. To find out more, visit:
www.global-engage.com
Michael Snyder is a Professor, Chair of Genetics and Director of the Stanford Center for Genomics and Personalized Medicine at Stanford University. In this presentation Michael discusses using omics and big data to predict disease risk and catch early disease onset.
The Dog Collar project is a citizen science project encouraging pet owners to understand better their animal while contributing to research.
This is an open hardware collar containing motion sensors (3d gyroscope and accelerometers) to measure the activity of a dogs. An onboard memory and battery will allow data to be stored for days. A bluetooth module allow synchronisation with moibile devices and computers.
Dog owners will be able to know if their dog exercice enought and what he is doing along the day. As it is an open source projet dog owners are always owners of their data and can choose to share or not anonymized data with researchers. Those data are very usefull for research on aging as dog age in 20 in the same way as humans in 80 years. Moreover dog have a quite know genotype and so researchers will be able to correlate genotype phenotype and environemental factors on a large scale.
There is also an educational project aiming at childrens : the idea is to bring the children to be more curious about nature around. They learn new things about animals by observing their dog.
The Human Cell Atlas Data Coordination PlatformLaura Clarke
This presentation gives a brief summary of the Human Cell Atlas project and describes the data coordination platform which is being built to support it.
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.
Multi-source connectivity as the driver of solar wind variability in the heli...Sérgio Sacani
The ambient solar wind that flls the heliosphere originates from multiple
sources in the solar corona and is highly structured. It is often described
as high-speed, relatively homogeneous, plasma streams from coronal
holes and slow-speed, highly variable, streams whose source regions are
under debate. A key goal of ESA/NASA’s Solar Orbiter mission is to identify
solar wind sources and understand what drives the complexity seen in the
heliosphere. By combining magnetic feld modelling and spectroscopic
techniques with high-resolution observations and measurements, we show
that the solar wind variability detected in situ by Solar Orbiter in March
2022 is driven by spatio-temporal changes in the magnetic connectivity to
multiple sources in the solar atmosphere. The magnetic feld footpoints
connected to the spacecraft moved from the boundaries of a coronal hole
to one active region (12961) and then across to another region (12957). This
is refected in the in situ measurements, which show the transition from fast
to highly Alfvénic then to slow solar wind that is disrupted by the arrival of
a coronal mass ejection. Our results describe solar wind variability at 0.5 au
but are applicable to near-Earth observatories.
Richard's aventures in two entangled wonderlandsRichard 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.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
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.
3. Do these associations reflect causal
relationships?
Key components to study causal relationships:
Data on genetic variants
Data on health
Data on sleep behavior => Traditionally based on error prone self-reported sleep
UK Biobank (N=103,000) raw data accelerometer offers an unparalleled opportunity to
investigate sleep
Wrist worn Axivity AX3 device
z
x
y
Tri-axial device
4. Objectives
1. Develop a method to detect sleep patterns
2. Find genetic variants associated with detected sleep patterns
3. Perform causality analyses
5. Our heuristic ‘sleep’ detection
Better name: Sustained inactivity bout
Interpretable as lack of posture change and lack
of movement, regardless of agreement with
neurological sleep
Angle is a more visual concept than magnitude
of acceleration
Embedded in Open Source R package GGIR
https://github.com/wadpac/GGIR
https://CRAN.R-project.org/package=GGIR
[van Hees et al. PLoSONE 2015, doi: 10.1371/journal.pone.0142533]
< 5º
> 5 minutes
6. Sleep Period Time-window
= sustained inactivity bouts
𝑥1 𝑥2 𝑥3 𝑥4-6 𝑥7 𝑥8
van Hees et al. PLoS One 2015 & van Hees et al. Scientific Reports 2018
Separating daytime inactivity/sleep
7. • No convincing gold standard exists for free-living conditions
• Heuristic method, ‘trained’ with unlabeled data from 20 random individuals.
Change in wrist angle over time invariant to sensor orientation
Threshold per
individual
My assumptions about what a sleep period is
[van Hees et al. Scientific Reports 2018, doi:10.1038/s41598-018-31266-z]
Sleep Period Time (SPT) Window
8. Method Evaluation
Sleep diary Polysomnography, one night
Older adults
(N=3750)
Sleep clinic
patients (N=28)
Healthy good
sleepers (N=22)
Mean Absolute Error
in sleep onset and waking time
40 minutes 71 minutes 38 minutes
Bias in estimated
Sleep Duration
- +30 minutes
(P=0.04, DF=27)
-6 minutes
(P=0.56, DF=21)
[van Hees et al. Scientific Reports 2018, doi:10.1038/s41598-018-31266-z]
10. L5 timeSleep midpoint
Sleep duration
variability
Sleep efficiency
Diurnal
inactivity
M10 time
No. of sleep
episodes
HTR1F
APOE
GPR139
KCNQ5
KCNH5
MEIS1
PAX8
ANK1
ALG10B
BTBD9
RGS16
MEIS1
MEIS1
PAX8
KCNH5
BTBD9
ALG10B
HTR1A
RELN
Up to 85,670 participants
~12 million HRC-imputed
genetic variants
hG
2: heritability estimate
hG
2=0.10 hG
2=0.09 hG
2=0.12
hG
2=0.19 hG
2=0.15
hG
2=0.03
hG
2=0.13 hG
2=0.22
Sleep duration
Jones, van Hees, et al., Nature Communications 2019
Replication in
6000 individuals
from CoLaus,
Whitehall and
Rotterdam
studies
Through genome-wide association analyses (GWAS)
we identify 47 distinct loci associated with our sleep
measures (P<5x10-8)
11. Insomnia causes an increased risk of
coronary artery disease
2 Sample MR IVW_P = 2x10-4
1 Sample MR IVW_P = 1x10-12
Lane et al. Nature Genetics 2019,
doi: 10.1038/s41588-019-0361-7
12. Being an early bird reduces risk of
schizophrenia and depression
Jones et al. Nature
Communications 2019, doi:
10.1038/s41467-018-08259-7 SNP effect on morningness
SNPeffectonschizophrenia(PGC)
2 Sample MR IVW_P = 1x10-4
13. Discussion points
Meaning daytime sustained inactivity bouts => naps?
If feasible, use longer measurements in future studies: 7 days is just a snapshot in time.
[*Wilkinson et al. Scientific Data 2016
14. Key underlying developments
1. Since 2007 wrist-worn Raw Data Accelerometry was advocated and explored by various
people in the field.s
2. Heuristic / interpretable sapproach to data analysis
3. Open Source Software, e.g. R package GGIR, 2012- present
15. Open Source Software (OSS) – Why?
Reproducibility
Software quality increases with more users and contributors
Effective use of (public) research funding
Usage not tight to developer: GGIR used in 100+ publications, I am co-author on ≈10
Making software Open Source can be embarrassing,
but not doing it is even more embarrassing!
Scientific publications become anecdotes if data and software are not available
16. Open Source Software – How & Who?
How?
Put your source code online as early as possible in the development, e.g. via GitHub
Use version control, e.g. git, to enable going back to specific time points
Include an Open Source License file => Otherwise it is still copyright protected
Document your code
Who should feel responsible for sustainability?
Community: Developer + End-users
17. Also very important …
Make research data more Findable, Accessible, Interoperable, and
Reproducible (FAIR)*
More recognition for Research Software Engineers:
We are an integral part of scientific advancement
Initiatives world-wide: https://rse.ac.uk/, http://nl-rse.org/, https://us-rse.org/,
https://www.de-rse.org, http://nordic-rse.org/, https://www.software.ac.uk
[*Wilkinson et al. Scientific Data 2016
18. Take home messages
Sleep measures:
can be extracted from wrist-worn raw data accelerometry
can be interpretable
have provided new insights in the relationship between sleep and health
Open source software and the people who develop it are critical for the
advancement of the physical behavior research field
