The geologic time scale (GTS) is a system of chronological dating that relates geological strata (stratigraphy) to time. Geologists have divided Earth's history into a series of time intervals. These time intervals are not equal in length like the hours in a day. Instead the time intervals are variable in length. This is because geologic time is divided using significant events in the history of the Earth.
The geologic time scale (GTS) is a system of chronological dating that relates geological strata (stratigraphy) to time. Geologists have divided Earth's history into a series of time intervals. These time intervals are not equal in length like the hours in a day. Instead the time intervals are variable in length. This is because geologic time is divided using significant events in the history of the Earth.
The extinction of a large number of species within a relatively short period of geological time thought to be due to factors such as a catastrophic global event or widespread environmental change that occurs too rapidly for most species to adapt
In this Presentation, I tried to give an overview of Five Mass Extinctions happened till now.
Are we witnessing the emergence of a new geological epoch?
Register to explore the whole course here: https://school.bighistoryproject.com/bhplive?WT.mc_id=Slideshare12202017
The extinction of a large number of species within a relatively short period of geological time thought to be due to factors such as a catastrophic global event or widespread environmental change that occurs too rapidly for most species to adapt
In this Presentation, I tried to give an overview of Five Mass Extinctions happened till now.
Are we witnessing the emergence of a new geological epoch?
Register to explore the whole course here: https://school.bighistoryproject.com/bhplive?WT.mc_id=Slideshare12202017
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.
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.
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.
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.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
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.
1. Name _______________________ Date________________________ Period _____ Score out of 25 ____
Corrected by ________________________
Geological Timeline Activity
Significant developments and extinctions of plant and
animal life can be shown on a geologic time scale.
To understand evolution, humans must think in units of time much larger than those we use to define our
lives. After all, evolutionary change occurs too slowly to be measured in days, months, or years. Instead,
it's documented in layers upon layers of rock deposited over the course of 4.6 billion years.
The earth has been significantly altered during this time by climate swings, volcanism, drifting continents,
and other "earth shattering" events. These dynamic conditions, in turn, have influenced every living thing
that has inhabited the planet. Because of this, biology alone cannot fully explain the evolution of life on
our planet. It's necessary to include the physical sciences -- geology, chemistry, and physics -- in order to
understand the conditions in which life arose and evolved.
The story of life is told primarily by its victims. Scientists say that only one in a thousand species that
have ever lived survives today. The other 99.9 percent are extinct, gone forever. With few exceptions, the
lifespan of individual species is short by geological standards, on average between 2 and 10 million years.
No matter how well adapted a creature is to its environment, history has shown that even the most
dominant can be wiped away. Ironically, extinction is a springboard to other life. Even in the most
catastrophic of events, species survive and continue to evolve, often filling niches left by the victims.
Extinction is by and large a natural process in which species, groups, and even whole families of
organisms disappear. Background extinctions, which are ongoing throughout the history of life, eliminate
one family every million years or so. The more destructive and relatively sudden kind of extinction -- the
mass extinction event -- is caused by environmental influences and has a global impact on diversity. All
extinctions identified in this timeline are mass extinction events.
The geologic time scale we use to study the history of the earth and of it life forms is commonly referred
to as "deep time," and it's a concept perhaps as difficult to conceive as deep space. Can humans measure
deep time? Yes. Will we ever truly comprehend such immensity of time? Probably not. But to develop a
better understanding of evolutionary change in its proper historical context, we must try. This timeline
provides a framework for doing so.
Procedure to make a Geological Timeline of Major Events
1. Work in a group of four students.
2. Lay the adding machine tape on the floor where it won’t interfere with other students. Tape the
ends to the floor.
3. Within the first 20 centimeters in the top left corner:
a. Write a full heading – Geological Timeline, names in the group, date, and period
b. Underneath the heading, make a scale. 1 meter = 1 billion years
1 centimeter = 10 million years
1 millimeter = 1 million years
4. Measurement for the timeline will begin with “Today, Starting on the left side of the paper,
measure 20 cm to the right on the line, and make a vertical mark. Label this mark – Today
Today
5. Using the Major Events listed in Table 1, measure and write the major events on your geologic
time line.
6. Each student will answer the Analysis questions; however, you will turn in one timeline per group.
2. Table 1 Major Events in Geological Time
Time Scale Major Event
Today 0 cm The Present
CENOZOIC
ERA
(write
in
blue)
~100,000 ya 0.1 mm Homo Sapiens (Modern Form of Human Species)
~ 22 mya 2.2 cm Grasses
~ 33 mya 3.3 cm First Apes
~50 mya 5 cm Eohippus (First Known Horse)
65 mya 6.5 cm CENOZOIC ERA
~ 65 mya 6.5 cm Dinosaurs Extinction
MESOZOIC
ERA
(write
in
red)
~140 mya 14 cm First Flowering Plants
~200 mya 20 cm Earthworms
~220 mya 22 cm First Mammals
~240 mya 24 cm Start of the age of the dinosaurs
248 24.8 cm MESOZOIC ERA
~330 mya 33 cm Winged Insects
PALEOZOIC
ERA
(write
in
green)
~380 mya 38 cm First Insects
~390 mya 39 cm First Sharks
~395 mya 39.5 cm Amphibians
~400 mya 40 cm Ferns
~440 mya 44 cm First Land Plants
~440 mya 44 cm First Jawed Fish
540 MYA 54 cm PALEOZOIC ERA
~550 mya 55 cm Jellyfish
PRECAMBR
IAN
TIME
(write
in
orange)
~1.8 bya 1 m 8 cm First Eukaryotes
~2.4 bya 2 m 40 cm Significant rise in oxygen, to ~2% level
~3.5 bya 3 m 50 cm Prokaryotes (bacteria)
~4.6 bya 4 m 60 cm Formation of Earth and Moon
4.6 bya 4 m 60 cm PRECAMBRIAN TIME
Analysis
1. For how long has there been life on Earth? _____________________________________________
2. For what percentage of time has life existed on Earth (round to the nearest whole number).
_______________________________________________________________________________
3. For about how many years of geological time have humans existed on Earth?
_______________________________________________________________________________
4. For about how many years of geological time have the dinosaurs existed on Earth?
_______________________________________________________________________________
5. Did dinosaurs exist at the same time as humans? _______________________________________
6. How do scientists determine when an era begins and when it ends?
_______________________________________________________________________________
_______________________________________________________________________________
7. What is the purpose of making a geological timeline?
_______________________________________________________________________________
_______________________________________________________________________________
