Medical genetics is a branch of human genetics confined to studying structure and function of the genetic material in health and disease states of human beings.
Based in Tijuana, Mexico, Oasis of Hope is a medical facility that provides patients with alternative cancer treatments. For close to six decades, Oasis of Hope has focused on going beyond chemotherapy to explore alternative cancer treatments, including the dendritic cancer (DC) vaccine.
The dendritic cancer vaccine is produced by scientists where dendritic cells are grown alongside cancer cells in a laboratory setting. Dendritic cells are designed to assist the immune system in discovering and destroying abnormal cells, including cancer cells.
The role of the DC vaccine is to stimulate a patient’s immune system to target and attack cancer. Unlike traditional vaccines that protect patients from contracting a disease, cancer treatment vaccines are administered to patients with cancer. To make DC vaccines, dendritic cells are removed from a patient then exposed to digested tumor peptides or messenger RNA obtained from a cancer patient’s tumor. After that, the primed dendritic cells are returned to the patient with the expectation that they will effectively activate immune responses.
Initially, DC clinical trials were unsatisfactory, but as knowledge increases, newer and more advanced techniques are being evaluated to boost the efficacy of dendritic cell vaccines. Some of the techniques under investigation are alternative antigen combinations and dendritic cell optimal loading. Dendritic cell vaccines are a welcome addition for oncologists exploring alternative ways to fight cancer. However, the investigation is still underway to determine how to generate the best DC vaccines that can offer protection against tumor development and trigger tumor regression.
Medical genetics is a branch of human genetics confined to studying structure and function of the genetic material in health and disease states of human beings.
Based in Tijuana, Mexico, Oasis of Hope is a medical facility that provides patients with alternative cancer treatments. For close to six decades, Oasis of Hope has focused on going beyond chemotherapy to explore alternative cancer treatments, including the dendritic cancer (DC) vaccine.
The dendritic cancer vaccine is produced by scientists where dendritic cells are grown alongside cancer cells in a laboratory setting. Dendritic cells are designed to assist the immune system in discovering and destroying abnormal cells, including cancer cells.
The role of the DC vaccine is to stimulate a patient’s immune system to target and attack cancer. Unlike traditional vaccines that protect patients from contracting a disease, cancer treatment vaccines are administered to patients with cancer. To make DC vaccines, dendritic cells are removed from a patient then exposed to digested tumor peptides or messenger RNA obtained from a cancer patient’s tumor. After that, the primed dendritic cells are returned to the patient with the expectation that they will effectively activate immune responses.
Initially, DC clinical trials were unsatisfactory, but as knowledge increases, newer and more advanced techniques are being evaluated to boost the efficacy of dendritic cell vaccines. Some of the techniques under investigation are alternative antigen combinations and dendritic cell optimal loading. Dendritic cell vaccines are a welcome addition for oncologists exploring alternative ways to fight cancer. However, the investigation is still underway to determine how to generate the best DC vaccines that can offer protection against tumor development and trigger tumor regression.
Tools and Technology for Advancing Rare Disease Research and Drug DevelopmentCovance
This white paper discusses virtual mapping of natural histories, the application of predictive modeling to better understand comorbidities and disease progressions as well as linkage to longitudinal real-world data sets. The goal is to improve diagnosis of patients, improve the design and conducting of trials, and enable development of more treatment options for people living with rare diseases.
Can target-based drug discovery be reconciled with phenotypic assays in the context of drug repurposing? One of the questions discussed at the SLAS Drug Repurposing SIG meeting at SLAS2013.
Death prompts a review of gene therapy vectorLindsay Meyer
Case study and analysis of Targeted Genetics' adeno-associated virus, tgAAC94. Includes overview of clinical trial design, FDA action, NIH investigation, and outcomes surrounding the death of a patient enrolled in the investigational trial.
Computational challenges in precision medicine and genomicsGary Bader
Genomics is mapping complex data about human biology and promises major medical advances. In particular, genomics is enabling precision medicine, the use of a patient's genome and physiological state to improve therapeutic efficacy and outcome. However, routine use of genomics data in medical research is in its infancy, due mainly to the challenges of working with "Big data". These data are so complex and large that typical researchers are not able to cope with them. Collectively, these data require an understanding of many aspects of experimental biology and medicine to correctly process and interpret. Data size is also an issue, as individual researchers may need to handle tens of terabytes (genomes from a few hundred patients), which is challenging to download and store on typical workstations. To effectively support precision medicine, scientists from a wide range of disciplines, including computer science, must develop algorithms to improve precision medicine (e.g. diagnostics and prognostics), genome interpretation, raw data processing and secure high performance computing.
Tools and Technology for Advancing Rare Disease Research and Drug DevelopmentCovance
This white paper discusses virtual mapping of natural histories, the application of predictive modeling to better understand comorbidities and disease progressions as well as linkage to longitudinal real-world data sets. The goal is to improve diagnosis of patients, improve the design and conducting of trials, and enable development of more treatment options for people living with rare diseases.
Can target-based drug discovery be reconciled with phenotypic assays in the context of drug repurposing? One of the questions discussed at the SLAS Drug Repurposing SIG meeting at SLAS2013.
Death prompts a review of gene therapy vectorLindsay Meyer
Case study and analysis of Targeted Genetics' adeno-associated virus, tgAAC94. Includes overview of clinical trial design, FDA action, NIH investigation, and outcomes surrounding the death of a patient enrolled in the investigational trial.
Computational challenges in precision medicine and genomicsGary Bader
Genomics is mapping complex data about human biology and promises major medical advances. In particular, genomics is enabling precision medicine, the use of a patient's genome and physiological state to improve therapeutic efficacy and outcome. However, routine use of genomics data in medical research is in its infancy, due mainly to the challenges of working with "Big data". These data are so complex and large that typical researchers are not able to cope with them. Collectively, these data require an understanding of many aspects of experimental biology and medicine to correctly process and interpret. Data size is also an issue, as individual researchers may need to handle tens of terabytes (genomes from a few hundred patients), which is challenging to download and store on typical workstations. To effectively support precision medicine, scientists from a wide range of disciplines, including computer science, must develop algorithms to improve precision medicine (e.g. diagnostics and prognostics), genome interpretation, raw data processing and secure high performance computing.
Extrapolation of in vitro data to preclinical and.pptxARSHIKHANAM4
Extrapolation of in vitro data to preclinical.
the topic is included in m.pharmacy 1st sem syllabus. which is essential for the study and that include the details about how you deal with the preclinical data that will help to decide the NOEAL and LOEAL, the humane dose of the drug can be calculated and further formation is also done.
Talk delivered at Warwick Biomedical Engineering Seminar series 27 November 2014. Develops a theme emerging from a review in 2010:
J Watkins, A Marsh, P C Taylor, D R J Singer
Therapeutic Delivery, 2010, 1, 651-665
"Continued adherence to a single-drug single-target paradigm will limit the ability of chemists to contribute to advances in personalized medicine, whether they be in discovery or delivery"
clinical and preclinical approaches to drug discovery.Here we mainly deals with preclinical approaches, ie. Pharmacological approach and toxicological approach
Pre-discovery
Understand the disease
Target Identification
Choose a molecule to target with a drug
Target Validation
Test the target and confirm its role in the disease
Drug Discovery
Find a promising molecule (a “lead compound”)
that could become a drug
The evolution and spread of antibiotic resistance in bacteri.docxcherry686017
The evolution and spread of antibiotic
resistance in bacterial pathogens is a grow-
ing threat to public health. The frequency
of antibiotic resistance in many bacterial
pathogens is increasing around the world,
and the resulting failures of antibiotic ther-
apy cause hundreds of thousands of deaths
annually1. The hope of addressing this crisis
by developing new antibiotics is diminished
both by the low rate of novel antibiotic dis-
covery and by the likelihood that pathogens
will evolve resistance to novel antibiotics just
as they have to existing antibiotics. The long-
term threat, therefore, is just as much the
process of evolution as the microbial patho-
gens themselves. Although the use of anti-
biotics inevitably promotes resistance, the
rate of evolution depends on the genomic
background and treatment strategies. Thus,
understanding the genomics and evolution-
ary biology of antibiotic resistance could
inform therapeutic strategies that are both
effective and mitigate the future potential to
evolve resistance.
Antibiotic resistance can be acquired
either by mutation or by the horizontal
transfer of resistance-conferring genes,
often in mobile genetic cassettes. The rela-
tive contribution of these factors depends
on the class of antibiotic and on the genetic
plasticity of the bacterial species. For exam-
ple, Mycobacterium tuberculosis primarily
acquires antibiotic resistance through nucleo-
tide changes, whereas hospital-acquired
Enterobacteriaceae infections often pos-
sess multidrug resistance cassettes and may
also acquire nucleotide changes that confer
resistance to drugs that are not often resisted
by mobile elements, such as quinolones2.
Progress in DNA sequencing and
other genotyping technologies means that
the genotypes of pathogens will soon be
widely available in clinical as well as research
settings. Genotype-based antibiotic resist-
ance profiling is already faster and more
economical than phenotypic profiling in
select cases (for example, rifampicin resist-
ance in M. tuberculosis caused by nucleotide
substitutions, and methicillin resistance in
Staphylococcus aureus caused by a resistance
cassette), and over time therapeutic and
infection control strategies will more heavily
rely on information derived from genome
sequencing of the infecting agents3.
Importantly, genotypes can inform not
only on the current drug susceptibility of a
pathogen but also on its future potential to
evolve resistance and spread. For example,
sequencing could determine whether a drug-
susceptible strain carries precursors to resist-
ance genes (which are termed proto-resistance
genes4), such as drug-degrading enzymes
or efflux pumps, that might be mutated to
increase expression or to strengthen activity.
Sequencing could also determine whether
resistance cassettes may be only one mutation
away from increased potency or from the
capacity to resist other drugs related to
the originally resi ...
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.
(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.
Comparing Evolved Extractive Text Summary Scores of Bidirectional Encoder Rep...University of Maribor
Slides from:
11th International Conference on Electrical, Electronics and Computer Engineering (IcETRAN), Niš, 3-6 June 2024
Track: Artificial Intelligence
https://www.etran.rs/2024/en/home-english/
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
What are greenhouse gasses how they affect the earth and its environment what is the future of the environment and earth how the weather and the climate effects.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
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.
The ability to recreate computational results with minimal effort and actionable metrics provides a solid foundation for scientific research and software development. When people can replicate an analysis at the touch of a button using open-source software, open data, and methods to assess and compare proposals, it significantly eases verification of results, engagement with a diverse range of contributors, and progress. However, we have yet to fully achieve this; there are still many sociotechnical frictions.
Inspired by David Donoho's vision, this talk aims to revisit the three crucial pillars of frictionless reproducibility (data sharing, code sharing, and competitive challenges) with the perspective of deep software variability.
Our observation is that multiple layers — hardware, operating systems, third-party libraries, software versions, input data, compile-time options, and parameters — are subject to variability that exacerbates frictions but is also essential for achieving robust, generalizable results and fostering innovation. I will first review the literature, providing evidence of how the complex variability interactions across these layers affect qualitative and quantitative software properties, thereby complicating the reproduction and replication of scientific studies in various fields.
I will then present some software engineering and AI techniques that can support the strategic exploration of variability spaces. These include the use of abstractions and models (e.g., feature models), sampling strategies (e.g., uniform, random), cost-effective measurements (e.g., incremental build of software configurations), and dimensionality reduction methods (e.g., transfer learning, feature selection, software debloating).
I will finally argue that deep variability is both the problem and solution of frictionless reproducibility, calling the software science community to develop new methods and tools to manage variability and foster reproducibility in software systems.
Exposé invité Journées Nationales du GDR GPL 2024
Deep Software Variability and Frictionless Reproducibility
Population variation to drugs
1. Aim:
To enable understanding of the etiology of a disease and the variation of the effects of drugs in a
population.
Short description:
The unexpected side-effects that suddenly emerge in late phase clinical trials are costly and very
difficult to protect against.
A suggested way to address at least some of the problems is to phenotypically screen the drug in
question against a large set of primary cells that cover a large segment of the target population. A
suitable type of cells is the Human Umbilical Vein Endothelial Cell, HUVECs. HUVECs can be
passaged up to 8 times without losing the responsiveness to stimuli, such as cytokines and growth
factors and can be harvested from single individuals.
By using a pre-determined set of phenotypic assays covering a space in the transcriptome/proteome
of relevant size, it would be possible to see if the drug in question has a different type of activity in
any of the tested individual donor HUVECs. The breadth of biology that the selected assays cover
will be determining the possibility to identify differences in reactions to the drug. The identified
differences will cast light on previously unknown individual pharmacokinetics that can
subsequently be included as screening criteria in later projects.
To validate the hypothesis it would be ideal to acquire live primary cells from a set of patients that
has experienced defined and severe reactions to a drug. The set of cells would be queried against a
negative set of cells from patients with similar medical history but lacking adverse reactions to the
drug in question and thereby enable understanding of the etiology of the disease. Depending on the
actual disease in question and the quality of the data from the drug development, the needed size of
the patient cohort will differ.
If the hypothesis can be successfully validated, the method can be developed to screen large
population segments even before initiating a clinical trial. The suggested size of the cell collection
depends on the regulations from FDA regarding accepted frequency of side effects, i.e. if a
frequency of 1:10,000 is accepted then the collection of cells has to reflect this to a certain statistical
certainty. An aspect of the findings is the potential to generate a pre-defined set of assays that can
be used to test a patient before exposing to the drug in question.
The closest comparison is to use SNPs for drug specific variations.