Gangliosides (GA) are highly concentrated in the brain, particularly in the gray matter of the cerebral cortex. They carry most of the sialic acid in the central nervous system and play important roles in neural development, neuronal growth, message transmission between neurons, and myelination of neurons. Abnormal metabolism of sphingolipids like GA can cause several neurological disorders characterized by mental retardation and neurological deficits. The lipid content of myelin is much higher than that of gray and white matter, with more cerebrosides and cholesterol. GA levels increase with brain development and are thought to be important for optimal neuronal function.
GPCRs are the most dynamic and most abundant all the receptors. The G protein-coupled receptor (GPCR) superfamily comprises the largest and most diverse group of proteins in mammals. GPCRs are responsible for every aspect of human biology from vision, taste, sense of smell, sympathetic and parasympathetic nervous functions, metabolism, and immune regulation to reproduction. GPCRs interact with a number of ligands ranging from photons, ions, amino acids, odorants, pheromones, eicosanoids, neurotransmitters, peptides, proteins, and hormones.
Nevertheless, for the majority of GPCRs, the identity of their natural ligands is still unknown, hence remain orphan receptors.
The simple dogma that underpins much of our current understanding of GPCRs, namely,
one GPCR gene− one GPCR protein− one functional GPCR− one G protein −one response
is showing distinct signs of wear.
GPCRs are the most dynamic and most abundant all the receptors. The G protein-coupled receptor (GPCR) superfamily comprises the largest and most diverse group of proteins in mammals. GPCRs are responsible for every aspect of human biology from vision, taste, sense of smell, sympathetic and parasympathetic nervous functions, metabolism, and immune regulation to reproduction. GPCRs interact with a number of ligands ranging from photons, ions, amino acids, odorants, pheromones, eicosanoids, neurotransmitters, peptides, proteins, and hormones.
Nevertheless, for the majority of GPCRs, the identity of their natural ligands is still unknown, hence remain orphan receptors.
The simple dogma that underpins much of our current understanding of GPCRs, namely,
one GPCR gene− one GPCR protein− one functional GPCR− one G protein −one response
is showing distinct signs of wear.
introduction
pituitary gland hormone
factor affecting secretion
function
regulation of secretion of prolactin
causes and symptoms of hypoprolactinaemia
causes and symptoms of hyperprolactinaemia
diagnosis
treatment
mechanism of prolactin
role of prolactin
uses
A catecholamine is a monoamine, an organic compound that has a catechol (benzene with two hydroxyl side groups at carbons 1 and 2) and a side-chain amine. Included among catecholamines are epinephrine (adrenaline), norepinephrine (noradrenaline), and dopamine. Release of the hormones epinephrine and norepinephrine from the adrenal medulla of the adrenal glands is part of the fight-or-flight response.
1- metabolism of the brain (I) 2012-13.pdfMohamed Afifi
Cells of the nervous system: Neurons & Glial cells
▫ Neurons:
A neuron is Formed of:
Cell body:
▫ contains most of the cytoplasm & organelles
Cytoplasmic extensions:
▫ include an axon & many dendrites
Overvie
introduction
pituitary gland hormone
factor affecting secretion
function
regulation of secretion of prolactin
causes and symptoms of hypoprolactinaemia
causes and symptoms of hyperprolactinaemia
diagnosis
treatment
mechanism of prolactin
role of prolactin
uses
A catecholamine is a monoamine, an organic compound that has a catechol (benzene with two hydroxyl side groups at carbons 1 and 2) and a side-chain amine. Included among catecholamines are epinephrine (adrenaline), norepinephrine (noradrenaline), and dopamine. Release of the hormones epinephrine and norepinephrine from the adrenal medulla of the adrenal glands is part of the fight-or-flight response.
1- metabolism of the brain (I) 2012-13.pdfMohamed Afifi
Cells of the nervous system: Neurons & Glial cells
▫ Neurons:
A neuron is Formed of:
Cell body:
▫ contains most of the cytoplasm & organelles
Cytoplasmic extensions:
▫ include an axon & many dendrites
Overvie
Etiology of TAU & PLAQUE protein in Alzheimer's Disease PintuLaskar
Details of Alzheimer's Disease and Etiology of Protein.
Under the guidance of
Mr. Nilanjan Adhikari
Assistant professor,Department of Pharmacology
P.G INSTITUTE OF MEDICAL SCIENCES
POWERPOINT PRESENTATION ON PATHOPHYSIOLOGY OF ALZHEIM.docxstilliegeorgiana
POWERPOINT PRESENTATION ON:
PATHOPHYSIOLOGY OF ALZHEIMER'S DISEASE
TANIA GONZALEZ DIAZ
WALDEN UNIVERSITY
NURS:6501C
AUGUST 03,2019
*
Alzheimer’s disease
Alzheimer disease (AD) is: Chronic neurodegenerative disorder
The leading cause of dementia
According to Etindele Sosso, Nakamura & Nakamura (2017), as of 2015, 29.8 million people had AD.
Most prevalent among people whose ages are 65 years and above.
Alzheimer disease (AD) is a chronic neurodegenerative disorder that normally starts and gradually progresses with the brain cells dying off. Leading to memory loss. The leading cause of dementia which affects an individual cognitive, social and behavioral skills that destroy the capability of a person to function properly.According to Etindele Sosso, Nakamura & Nakamura (2017), as of 2015, there were 29.8 million people globally who had AD. It mostly starts in people whose ages are over 65 years.
*
Pathophysiology of Alzheimer’s Disease Exact cause is unknown. Early onset of Familial Alzheimer’s Disease is associated with 3 genes found in chromosome 21, namely; Abnormal amyloid precursor protein 14 [APP14] Abnormal presenilin 1 [PSEN1] andAbnormalpresenilin 2 [PSEN2])Late onset of AD is related to changes in apolipoprotein E gene-allele4(APOE4) gene found in chromosome 19. Source: (Huether, McCance, Brashers & Rote, 2016)
The exact cause of AD is still unknown till date. Early onset of Familial Alzheimer’s Disease is associated with 3 genes found in chromosome 21, namely; Abnormal amyloid precursor protein 14 [APP14] Abnormal presenilin 1 [PSEN1] andAbnormalpresenilin 2 [PSEN2])Late onset of AD is related to changes in apolipoprotein E gene-allele 4 (APOE4) gene found in chromosome 19.
*
Pathophysiology of Alzheimer’s Disease …contdDNA methylation is one epigenetic markers for AD.Pathological alterations in the brain causes the loss of memory.These pathological alterations include; Accumulation of extracellular neuritic plaques with core of amyloid Degeneration of basal forebrain ß-protein Intraneuronal neurofibrillary tanglescholinergic neurons with loss of acetylcholineSource: (Huether, McCance, Brashers & Rote, 2016)
DNA methylation is one epigenetic markers for AD.Pathological alterations in the brain causes the loss of memory.These pathological alterations include; Accumulation of extracellular neuritic plaques with core of amyloid ß-protein Intraneuronal neurofibrillary tanglesDegeneration of basal forebrain cholinergic neurons If the brain is unable to get rid of amyloid the precursor protein, toxic fragments of amyloid ß-protein accumulates and which trigger neuritic plaques to diffuse, the transmission of impulses by nerve cells to be disrupted and the nerve cells to die. The tau protein in neiurons detaches forming an insoluble neurofibrillary tangles, which causes the neurons to die. Neurofibrilary tangles and neuritic plaques which are more concentrated in the cerebral cortex are the one that contribute t ...
Alzheimer's disease is a causes a progressive loss of brain cells leading to memory loss. In this slide we will learn about its causes,symptoms, pathophysiology, treatment, medication and risk factors.
OMEGA 3 FATTY ACIDS AND ALZHEIMER'S DISEASEBabie Maibam
Prevention of age-related cognitive decline - a public health challenge.Nutrition, a major lifelong environmental factor, offers promising perspectives.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
hematic appreciation test is a psychological assessment tool used to measure an individual's appreciation and understanding of specific themes or topics. This test helps to evaluate an individual's ability to connect different ideas and concepts within a given theme, as well as their overall comprehension and interpretation skills. The results of the test can provide valuable insights into an individual's cognitive abilities, creativity, and critical thinking skills
DERIVATION OF MODIFIED BERNOULLI EQUATION WITH VISCOUS EFFECTS AND TERMINAL V...Wasswaderrick3
In this book, we use conservation of energy techniques on a fluid element to derive the Modified Bernoulli equation of flow with viscous or friction effects. We derive the general equation of flow/ velocity and then from this we derive the Pouiselle flow equation, the transition flow equation and the turbulent flow equation. In the situations where there are no viscous effects , the equation reduces to the Bernoulli equation. From experimental results, we are able to include other terms in the Bernoulli equation. We also look at cases where pressure gradients exist. We use the Modified Bernoulli equation to derive equations of flow rate for pipes of different cross sectional areas connected together. We also extend our techniques of energy conservation to a sphere falling in a viscous medium under the effect of gravity. We demonstrate Stokes equation of terminal velocity and turbulent flow equation. We look at a way of calculating the time taken for a body to fall in a viscous medium. We also look at the general equation of terminal velocity.
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.
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
Phenomics assisted breeding in crop improvementIshaGoswami9
As the population is increasing and will reach about 9 billion upto 2050. Also due to climate change, it is difficult to meet the food requirement of such a large population. Facing the challenges presented by resource shortages, climate
change, and increasing global population, crop yield and quality need to be improved in a sustainable way over the coming decades. Genetic improvement by breeding is the best way to increase crop productivity. With the rapid progression of functional
genomics, an increasing number of crop genomes have been sequenced and dozens of genes influencing key agronomic traits have been identified. However, current genome sequence information has not been adequately exploited for understanding
the complex characteristics of multiple gene, owing to a lack of crop phenotypic data. Efficient, automatic, and accurate technologies and platforms that can capture phenotypic data that can
be linked to genomics information for crop improvement at all growth stages have become as important as genotyping. Thus,
high-throughput phenotyping has become the major bottleneck restricting crop breeding. Plant phenomics has been defined as the high-throughput, accurate acquisition and analysis of multi-dimensional phenotypes
during crop growing stages at the organism level, including the cell, tissue, organ, individual plant, plot, and field levels. With the rapid development of novel sensors, imaging technology,
and analysis methods, numerous infrastructure platforms have been developed for phenotyping.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
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 Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
2. Gangliosides (GA)of the Brain
The brain and central nervous
system (CNS) contains
considerable levels of GA
In infancy (10% of the total lipid
mass of the brain is GA).
GA also carry the majority of
the sialic acid within the CNS.
3. Within the CNS, Gangliosides(GA)
are found in the highest
concentrations in the Cerebral
Cortex of the brain’s Grey Matter
(15 times that of other organs such
as the liver, lungs and spleen).
3 times more GA in Grey Matter
than White Matter.
The Grey Matter is responsible for
higher thought, learning and
memory
4. Functions of Gangliosides in
brain
Gangliosides: are components of
the central nervous system,
including the brain.
Gangliosides: are components of
brain neurons.
Gangliosides carry most of the
Sialic acid within the brain.
GA are naturally found in breast
milk, and therefore thought to be
important for optimal development
5. GA are highly concentrated in the
brain, where they may play a role
in assisting in important neuronal
functions.
Brain development/growth is
associated with an increase in brain
Gangliosides concentration
GA are thought to play an
important role in intestinal
immunity development in the
neonate
6. In Neural development
As already mentioned, studies have
shown that dietary GA are able to be
taken up by the body and incorporated
into the brain in the same way as GA
that are formed within the body.
i.e. the content of GA in the developing
retina increases rapidly with increasing
dietary GA intake; the same has been
found for nerve cells.
Brain GA is found within nerve cells in
Grey Matter, and are therefore thought
to assist in the important functions of
7. 2. Neuronal growth & message
transmission
GA are required for normal axonal and dendritic
(projections from the neuron) development and growth
within neurons.
As they increase the number of neurons they therefore
are also involved in synapse (space between neurons)
formation.
8. A lack of sufficient gangliosides has
been shown to result in a striking
loss of new axons and dendrites.
GA are also thought to be important
for message transmission by
controlling neurotransmitter release.
Neurotransmitters are required to
keep the signals going (i.e. to jump
the ‘gaps’ between neurons).
As neurons successfully fire, one to
the next, they create a circuit that
can process new information.
11. Myelination is important
for……..1. The major function of myelin membranes
in the brain is to insulate axons (the body
of the neuron) and provide high
conductivity of messages within the brain,
essentially allowing the message to travel
faster.
2. High conductivity is important for
neuronal communication, which is
essential for brain functions.
3. Myelin insulates the axon and helps the
message travel faster between neurons –
ultimately resulting in faster
12. nucleus of Schwann cell
cytoplasm of axon The cell membranes
are compressed
together to form a
tightly packed layer of
myelin which is rich in a
particular type of
membrane
It acts as an insulator
to prevent the
movement of ions
across the cell
membrane and so acts
as an insulator which
speeds up the speed of
transmission of nerve
impulses
13. Many neurones also have a myelin sheath around the axon – called
myelinated neurones.It is formed by specialised cells called Schwann
cells which wrap around the axon
17. What is the function of myelin
sheath?
Myelin sheath makes the conduction
of nerve impulse faster by
SALTATORY CONDUCTION.
In this type of conduction the
impulse jumps through the NODES
OF RANVIER and so the chances of
leakage is also minimized.
18. WHITE AND GREY MATTER
OF BRAIN
The central nervous system is
composed of white matter and
gray matter.
White matter is so named
because the density of lipid-rich
myelinated axons gives the tissue
a white appearance.
Grey matter contains perikaryons
(less lipid) and appears darker.
21. Are lipids the source of energy in
nervous tissue?
No lipids do not provide energy to the
brain cells or nervous tissue as BETA
OXIDATION of fatty acids do not take
place in nervous tissue.
So how the neurons get
energy???????
They gets the energy from the ketone
bodies that is b-hydroxybutyric acid
acetoacetic acids and branched chain
amino acid like VALINE in case of
starvation.
22. Disorders Associated with Abnormal Sphingolipid Metabolism
Disorder Enzyme Deficiency Accumulating Substance Salient Features
Tay-Sachs
disease
Hexoseaminidase A GM2 ganglioside
Incidence 1 in 6000 births .infantile form:
rapidly progressing mental retardation,
blindness, early mortality 3 -4 yrs
Sandhoff
disease
HexoseaminidaseA
and B
Globoside
Infantile form- Neurological deficit and
mental retardations.Same Symptoms as
Tay Sachs
Tay-Sachs AB
variant
GM2 activator
deficiency
GM2 activator
(GM2A)
GM2 ganglioside
infantile form: same symptoms as Tay-
Sachs
Gaucher
disease
Acid β-glucosidase
(glucocerebrosidase)
Glucocerebrosides
hepatosplenomegaly, mental retardation in
infantile form, long bone degeneration
Fabry disease α-galactosidase A Ceramide trihexosesides Kidney failure, skin rashes. Death by 5 yrs
Niemann-Pick
diseases
Types A and B
Type C
sphingomyelinase
NPC1 protein
sphingomyelins
LDL-derived cholesterol
type A is severe disorder with
heptosplenomegaly, severe neurological
involvement leading to early death, type B
only visceral involvement
24. Lipid Content of Grey and White Matter
Grey matter, white matter, and
myelin were isolated from the frontal
lobes of humans aged 10 months, 6
yr, 9 yr, and 55 yr and the lipid
compositions of each were
determined.
Myelin had a much higher lipid
content (78-81% of the dry weight)
than white matter (49-66%) or grey
matter (36-40%).
25. Myelin Content
Myelin contained much higher molar
percentages of cerebroside and
cerebroside sulfate
Slightly higher molar percentages of
cholesterol, and lower molar
percentages of ethanolamine
glycerophosphatides and choline
glycerophosphatides than grey matter.
The molar percentages of serine
glycerophosphatides and sphingomyelin
were about the same in each tissue.
26. The Aldehyde content of
Glycerophosphatides
Expressed as molar percentage of
the total lipoidal residues in each
lipid, were as follows:
Ethanolamine glycerophosphatides
from myelin 40-50%;
Ethanolamine glycerophosphatides
from grey matter 21-27%;
27. serine glycerophosphatides from
myelin 21-36%;
serine glycerophosphatides from grey
matter 0.3-3.8%.
Choline glycerophosphatides from
either tissue contained only traces of
aldehydes.
The extra-myelin portion of white matter
had a lipid composition that was very
similar to that of myelin, but quite
different from that of grey matter.