This document summarizes the WikiPathways online pathway database and analysis tools. It provides statistics on WikiPathways, including the number of human pathways and genes covered. It also describes WikiPathways' data formats and web services, and highlights related tools for pathway analysis and visualization like PathVisio and Cytoscape apps. Usage tips are given for navigating the WikiPathways editor and tutorial.
Cystic Fibrosis is an autosomal recessive genetic disease that is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, which has important roles in ion exchange.
Cystic Fibrosis is an autosomal recessive genetic disease that is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene, which has important roles in ion exchange.
National Resource for Networks Biology's TR&D Theme 3: Although networks have been very useful for representing molecular interactions and mechanisms, network diagrams do not visually resemble the contents of cells. Rather, the cell involves a multi-scale hierarchy of components – proteins are subunits of protein complexes which, in turn, are parts of pathways, biological processes, organelles, cells, tissues, and so on. In this technology research project, we will pursue methods that move Network Biology towards such hierarchical, multi-scale views of cell structure and function.
Technology R&D Theme 2: From Descriptive to Predictive NetworksAlexander Pico
National Resource for Networks Biology's TR&D Theme 2: Genomics is mapping complex data about human biology and promises major medical advances. However, the routine use of genomics data in medical research is in its infancy, due mainly to the challenges of working with highly complex “big data”. In this theme, we will use network information to help organize, analyze and integrate these data into models that can be used to make clinically relevant diagnoses and predictions about an individual.
National Resource for Networks Biology's TR&D Theme 1: In this theme, we will develop a series of tools and methodologies for conducting differential analyses of biological networks perturbed under multiple conditions. The novel algorithmic methodologies enable us to make use of high-throughput proteomic level data to recover biological networks under specific biological perturbations. The software tools developed in this project enable researchers to further predict, analyze, and visualize the effects of these perturbations and alterations, while enabling researchers to aggregate additional information regarding the known roles of the involved interactions and their participants.
The NRNB has been funded as an NIGMS Biomedical Technology Research Resource since 2010. During the previous five-year period, NRNB investigators introduced a series of innovative methods for network biology including network-based biomarkers, network-based stratification of genomes, and automated inference of gene ontologies using network data. Over the next five years, we will seek to catalyze major phase transitions in how biological networks are represented and used, working across three broad themes: (1) From static to differential networks, (2) From descriptive to predictive networks, and (3) From flat to hierarchical networks bridging across scales. All of these efforts leverage and further support our growing stable of network technologies, including the popular Cytoscape network analysis infrastructure.
Visualization and Analysis of Dynamic Networks Alexander Pico
DynNetwork development was taken up initially by Sabina Sara Pfister back in GSoC 2012. She laid out a strong foundation for dynamic network visualization in Cytoscape and my job was to extend the plugin’s functionality to help users analyse time changing networks. The two of us were mentored by Jason Montojo. We had developed a decent tool over the course of two GSoC programs to aid dynamic network analysis and our efforts culminated in DynNetwork getting accepted for an oral presentation at the International Network for Social Network Analysis (INSNA), Sunbelt 2014 which was held in St. Petersburg, FL in February.
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
National Resource for Networks Biology's TR&D Theme 3: Although networks have been very useful for representing molecular interactions and mechanisms, network diagrams do not visually resemble the contents of cells. Rather, the cell involves a multi-scale hierarchy of components – proteins are subunits of protein complexes which, in turn, are parts of pathways, biological processes, organelles, cells, tissues, and so on. In this technology research project, we will pursue methods that move Network Biology towards such hierarchical, multi-scale views of cell structure and function.
Technology R&D Theme 2: From Descriptive to Predictive NetworksAlexander Pico
National Resource for Networks Biology's TR&D Theme 2: Genomics is mapping complex data about human biology and promises major medical advances. However, the routine use of genomics data in medical research is in its infancy, due mainly to the challenges of working with highly complex “big data”. In this theme, we will use network information to help organize, analyze and integrate these data into models that can be used to make clinically relevant diagnoses and predictions about an individual.
National Resource for Networks Biology's TR&D Theme 1: In this theme, we will develop a series of tools and methodologies for conducting differential analyses of biological networks perturbed under multiple conditions. The novel algorithmic methodologies enable us to make use of high-throughput proteomic level data to recover biological networks under specific biological perturbations. The software tools developed in this project enable researchers to further predict, analyze, and visualize the effects of these perturbations and alterations, while enabling researchers to aggregate additional information regarding the known roles of the involved interactions and their participants.
The NRNB has been funded as an NIGMS Biomedical Technology Research Resource since 2010. During the previous five-year period, NRNB investigators introduced a series of innovative methods for network biology including network-based biomarkers, network-based stratification of genomes, and automated inference of gene ontologies using network data. Over the next five years, we will seek to catalyze major phase transitions in how biological networks are represented and used, working across three broad themes: (1) From static to differential networks, (2) From descriptive to predictive networks, and (3) From flat to hierarchical networks bridging across scales. All of these efforts leverage and further support our growing stable of network technologies, including the popular Cytoscape network analysis infrastructure.
Visualization and Analysis of Dynamic Networks Alexander Pico
DynNetwork development was taken up initially by Sabina Sara Pfister back in GSoC 2012. She laid out a strong foundation for dynamic network visualization in Cytoscape and my job was to extend the plugin’s functionality to help users analyse time changing networks. The two of us were mentored by Jason Montojo. We had developed a decent tool over the course of two GSoC programs to aid dynamic network analysis and our efforts culminated in DynNetwork getting accepted for an oral presentation at the International Network for Social Network Analysis (INSNA), Sunbelt 2014 which was held in St. Petersburg, FL in February.
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
Title: Sense of Smell
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 primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
Dr Sujoy Dasgupta presented the study on "Couples presenting to the infertility clinic- Do they really have infertility? – The unexplored stories of non-consummation" in the 13th Congress of the Asia Pacific Initiative on Reproduction (ASPIRE 2024) at Manila on 24 May, 2024.
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
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.
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
Here, is a typical pathway from WikiPathways. Like most textbook pathways, it depicts proteins and metabolites, reactions and complexes, and their localization into subcellular compartments. But each one of these rectangles is also a data object connected to a database of standard identifiers that can be mapped to a variety of datasets.
Here, for example, we’re seeing differential expression data with up- and down-regulated genes in yellow and blue. When a biologist looks at this, something very special happens. A little movie is triggered in their mind……the room goes quiet and their focus is drawn to a particular area of interest; they think about kinetics, rate-limiting factors, conditions and timing; they consider a number of "what if" scenarios: "what if this cascade of events……could be blocked by increasing this factor". This is in fact exactly what happens when we take statin drugs to lower our cholesterol. What I’m trying to illustrate here with ppt tricks is the act of visualization…
The data-mapped image is really just sitting there and all of this is just going on in the mind of the researcher, right? …the researcher takes in this visual data, which allows it to mix with all the other associations up there from prior observations they’ve made (the majority of which have not been published or put into textbooks).This wouldn’t be necessary if we could parameterize all these subtle associations……and model them all in a supercomputer. Then we could just mix in all known interactions, molecular concentrations and kinetic rates, and just read out the answers to our questions in concrete units of information. But this is not possible (at least not yet),… …so even though I’m a proponent of computational modeling and analysis, I’d argue that there are a number of situations where humans are actually still really important in data analysis.
Returning now to this basic unit of pathway information, the pathway diagram. How exactly are these models constructed? They do not come from direct measurement. It was assembled from a wide variety of data types and assays, a curated set of observations left intentionally sparse. This pathway, for example, is showing the mechanism of a common cancer drug called 5-FU: it's metabolized in the liver, it's byproducts enter the blood stream and are taken up by cancer cells where they disrupt key pathways for cell survival. But this pathway is not representing all that we know about this process and new data about these components and their interactions continues to pour in with no end in sight. So, all we know for sure is that this model will change over time as we fill-in details and learn what’s most relevant.
This is exactly what we had in mind when we started the WikiPathways project. It's a wiki, like wikipedia, but what we did is we ripped out the text editor and replace it with our own pathway drawing tool. So anyone can find a pathway, click 'edit', and then add new information [[like a new byproduct of 5-FU that also goes to cancer cells and triggers apoptosis]]. You then click ‘save’ and your changes are immediately available to the rest of the world. You can provide literature references to cite evidence for your changes. And the entire research community is your peer review group: they can approve or undo your changes. In this way, we can keep up with the flood of new data relating to biological processes.
When you’re editing a pathway, you are not only editing the diagram, you’re also editing a standard XML file that can be exchanged and accessed programmatically. For, the software developers in the audience, in addition to this XML formats, there is also web service access to the pathway content. You can programmatically return pathway images with highlighted nodes, for example. There is embed code to insert interactive pathway widgets into your own web sites, and we are starting to represent our pathway content as linked data to support semantic queries. The most common workflow today is to import the XML into tools like PathVisio and Cytoscape.
Putting it all together, you can begin to see how we are feeding into this virtuous cycle. Data is synthesized into pathway diagrams. And orthogonal data can be mapped onto these pathway models. Computational analysis, together with the act of visualization can lead to new explanations and new ideas.And finally, these new ideas can be tested to generate new data, bringing us back to synthesis. And I have to say, the wiki model really working well here…
We’ve been collecting and curating pathways since 2001. In the years just prior to launching WikiPathways we really struggled relying on our internal curation team alone. [This was our growth curve for number of pathways in blue and number of unique genes on those pathways in green]. In the years following the launch of WikiPathways we experienced a whole new level of growth. And this last year things are really starting to take off. I might have to start using logarithmic plots for the number of pathways. It’s difficult to quantity the effect on quality, but our curation team has been thrilled by the quality and overall improvements we’re seeing in the content. Basically, no internal team can curate all of biology; this task can only be done by a distributed system.
And in terms of participation, not only has the number users increased since our launch in 2008, but so has the number of contributors, averaging at around 22%. Putting pathway editing and curation tools into the hands of researchers is the best (and only) way to keep up with the flood of new data coming in; and they are actually using them! You only need to register if you want to edit, so we also have lots of folks viewing and downloading pathways: over1 million pageviews by over a quarter million unique visitors. And these numbers don’t include access through Cytoscape, embed code and web services. I know these numbers don’t compare to wikipedia, but come on, we’re talking about biological pathways here: a niche market within the niche market of systems biology.
There are help pages and contact links at WikiPathways that you can find in the left navigation panel, and this is where we are headed next for an interactive tutorial…
Work with tutorial example or your own pathway of interest!
After loading a pathway into Cytoscape, for example, you can then import your own dataset from an excel spreadsheet and define how you want your data to map in terms of color gradients. This process is dynamic and interactive, so you can explore your dataset in the context of these pathways. And, of course, in Cytoscape you can make use of all the other apps that are available to calculate shortest path, perform clustering or over-representation analysis.