Deer life cycle

•Download as PPTX, PDF•

0 likes•696 views

R

White-tailed deer have a life cycle where fawns are born and drink milk from their mothers to grow. The fawns then become yearlings after one year, still resembling the mother. Finally, the yearlings mature into adult deer after further growth.

Animals life
cycles
How can animals life cycles
differ?

Life cycle
How an animal starts life, grows to be an
adult, has young and dies.

White-tail deer
 The baby deer is called Fawn
 The fawn drinks
Milk from its mother
to grow up
 The fawn looks like
its mother

White-tail deer
 The fawn grows up
to a yearling
 The young deer is
called Yearling
 The yearling also
looks like its mother

White-tail deer
 The yearling grows up
to an Adult deer

Recommended

1 b float and sink

1 b float and sink

1 b float and sink

Maria powerpoint

Maria powerpoint

Maria powerpointMrMcWhertor

Animal life cycles1

Animal life cycles1

Animal life cycles1

Stem fun

Animal life cycles

Animal life cycles

Animal life cycles

1 a float and sink

1 a float and sink

1 a float and sink

2 a project

2 b project

Recommended

1 b float and sink

1 b float and sink

1 b float and sink

Maria powerpoint

Maria powerpoint

Maria powerpointMrMcWhertor

Animal life cycles1

Animal life cycles1

Animal life cycles1

Stem fun

Animal life cycles

Animal life cycles

Animal life cycles

1 a float and sink

1 a float and sink

1 a float and sink

2 a project

2 b project

1 b project

1 a project

Magnets 3

Mix. 1 a

Magnets1

Mixing 1 b

Magnets 2 b

Magnets 2 a

Seeds 2 a

Seeds 2 b

Plants life cycles

Plants life cycles

Plants life cycles

Butterfly life cycle

Butterfly life cycle

Butterfly life cycle

1 a nr

Sorting nr

Earth changes slowly

Earth changes slowly

Earth changes slowly

Earth changes quickly

Earth changes quickly

Earth changes quickly

Behavioral adaptation

Behavioral adaptation

Behavioral adaptation

Fall

Adaptation (body parts)

Adaptation (body parts)

Adaptation (body parts)

What happens to animals

What happens to animals

What happens to animals

Cancer cell metabolism: special Reference to Lactate Pathway

Cancer cell metabolism: special Reference to Lactate Pathway

Cancer cell metabolism: special Reference to Lactate Pathway

AADYARAJPANDEY1

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.

EY - Supply Chain Services 2018_template.pptx

EY - Supply Chain Services 2018_template.pptx

EY - Supply Chain Services 2018_template.pptx

More Related Content

More from roshanrm

1 b project

1 a project

Magnets 3

Mix. 1 a

Magnets1

Mixing 1 b

Magnets 2 b

Magnets 2 a

Seeds 2 a

Seeds 2 b

Plants life cycles

Plants life cycles

Plants life cycles

Butterfly life cycle

Butterfly life cycle

Butterfly life cycle

1 a nr

Sorting nr

Earth changes slowly

Earth changes slowly

Earth changes slowly

Earth changes quickly

Earth changes quickly

Earth changes quickly

Behavioral adaptation

Behavioral adaptation

Behavioral adaptation

Fall

Adaptation (body parts)

Adaptation (body parts)

Adaptation (body parts)

What happens to animals

What happens to animals

What happens to animals

More from roshanrm (20)

1 b project

1 a project

Magnets 3

Mix. 1 a

Magnets1

Mixing 1 b

Magnets 2 b

Magnets 2 a

Seeds 2 a

Seeds 2 b

Plants life cycles

Plants life cycles

Plants life cycles

Butterfly life cycle

Butterfly life cycle

Butterfly life cycle

1 a nr

Sorting nr

Earth changes slowly

Earth changes slowly

Earth changes slowly

Earth changes quickly

Earth changes quickly

Earth changes quickly

Behavioral adaptation

Behavioral adaptation

Behavioral adaptation

Fall

Adaptation (body parts)

Adaptation (body parts)

Adaptation (body parts)

What happens to animals

What happens to animals

What happens to animals

Recently uploaded

Cancer cell metabolism: special Reference to Lactate Pathway

Cancer cell metabolism: special Reference to Lactate Pathway

Cancer cell metabolism: special Reference to Lactate Pathway

AADYARAJPANDEY1

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.

EY - Supply Chain Services 2018_template.pptx

EY - Supply Chain Services 2018_template.pptx

EY - Supply Chain Services 2018_template.pptx

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...

We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and 30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1 . Our search finds no candidates at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to infer the properties of the evolving luminosity function without binning in redshift or luminosity that marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results, and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5 from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical models for evolution of the dark matter halo mass function.

Anemia_ different types_causes_ conditions

Anemia_ different types_causes_ conditions

Anemia_ different types_causes_ conditions

Unveiling the Energy Potential of Marshmallow Deposits.pdf

Unveiling the Energy Potential of Marshmallow Deposits.pdf

Unveiling the Energy Potential of Marshmallow Deposits.pdf

Erdal Coalmaker

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

Health Advances

Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...

Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...

Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

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.

Lateral Ventricles.pdf very easy good diagrams comprehensive

Lateral Ventricles.pdf very easy good diagrams comprehensive

Lateral Ventricles.pdf very easy good diagrams comprehensive

silvermistyshot

justice-and-fairness-ethics with example

justice-and-fairness-ethics with example

justice-and-fairness-ethics with example

plant biotechnology Lecture note ppt.pptx

plant biotechnology Lecture note ppt.pptx

plant biotechnology Lecture note ppt.pptx

SCHIZOPHRENIA Disorder/ Brain Disorder.pdf

SCHIZOPHRENIA Disorder/ Brain Disorder.pdf

SCHIZOPHRENIA Disorder/ Brain Disorder.pdf

SELF-EXPLANATORY

insect taxonomy importance systematics and classification

insect taxonomy importance systematics and classification

insect taxonomy importance systematics and classification

ESR_factors_affect-clinic significance-Pathysiology.pptx

ESR_factors_affect-clinic significance-Pathysiology.pptx

ESR_factors_affect-clinic significance-Pathysiology.pptx

In silico drugs analogue design: novobiocin analogues.pptx

In silico drugs analogue design: novobiocin analogues.pptx

In silico drugs analogue design: novobiocin analogues.pptx

Astronomy Update- Curiosity’s exploration of Mars _ Local Briefs _ leadertele...

Astronomy Update- Curiosity’s exploration of Mars _ Local Briefs _ leadertele...

Astronomy Update- Curiosity’s exploration of Mars _ Local Briefs _ leadertele...

NathanBaughman3

Predicting property prices with machine learning algorithms.pdf

Predicting property prices with machine learning algorithms.pdf

Predicting property prices with machine learning algorithms.pdf

Penicillin...........................pptx

Penicillin...........................pptx

Penicillin...........................pptx

FAIR & AI Ready KGs for Explainable Predictions

FAIR & AI Ready KGs for Explainable Predictions

FAIR & AI Ready KGs for Explainable Predictions

Michel Dumontier

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.

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

Recently uploaded (20)

Cancer cell metabolism: special Reference to Lactate Pathway

Cancer cell metabolism: special Reference to Lactate Pathway

Cancer cell metabolism: special Reference to Lactate Pathway

EY - Supply Chain Services 2018_template.pptx

EY - Supply Chain Services 2018_template.pptx

EY - Supply Chain Services 2018_template.pptx

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...

Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...

Anemia_ different types_causes_ conditions

Anemia_ different types_causes_ conditions

Anemia_ different types_causes_ conditions

Unveiling the Energy Potential of Marshmallow Deposits.pdf

Unveiling the Energy Potential of Marshmallow Deposits.pdf

Unveiling the Energy Potential of Marshmallow Deposits.pdf

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

The ASGCT Annual Meeting was packed with exciting progress in the field advan...

Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...

Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...

Circulatory system_ Laplace law. Ohms law.reynaults law,baro-chemo-receptors-...

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...

Lateral Ventricles.pdf very easy good diagrams comprehensive

Lateral Ventricles.pdf very easy good diagrams comprehensive

Lateral Ventricles.pdf very easy good diagrams comprehensive

justice-and-fairness-ethics with example

justice-and-fairness-ethics with example

justice-and-fairness-ethics with example

plant biotechnology Lecture note ppt.pptx

plant biotechnology Lecture note ppt.pptx

plant biotechnology Lecture note ppt.pptx

SCHIZOPHRENIA Disorder/ Brain Disorder.pdf

SCHIZOPHRENIA Disorder/ Brain Disorder.pdf

SCHIZOPHRENIA Disorder/ Brain Disorder.pdf

insect taxonomy importance systematics and classification

insect taxonomy importance systematics and classification

insect taxonomy importance systematics and classification

ESR_factors_affect-clinic significance-Pathysiology.pptx

ESR_factors_affect-clinic significance-Pathysiology.pptx

ESR_factors_affect-clinic significance-Pathysiology.pptx

In silico drugs analogue design: novobiocin analogues.pptx

In silico drugs analogue design: novobiocin analogues.pptx

In silico drugs analogue design: novobiocin analogues.pptx

Astronomy Update- Curiosity’s exploration of Mars _ Local Briefs _ leadertele...

Astronomy Update- Curiosity’s exploration of Mars _ Local Briefs _ leadertele...

Astronomy Update- Curiosity’s exploration of Mars _ Local Briefs _ leadertele...

Predicting property prices with machine learning algorithms.pdf

Predicting property prices with machine learning algorithms.pdf

Predicting property prices with machine learning algorithms.pdf

Penicillin...........................pptx

Penicillin...........................pptx

Penicillin...........................pptx

FAIR & AI Ready KGs for Explainable Predictions

FAIR & AI Ready KGs for Explainable Predictions

FAIR & AI Ready KGs for Explainable Predictions

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

GBSN - Biochemistry (Unit 5) Chemistry of Lipids

Deer life cycle

1. Animals life cycles How can animals life cycles differ?

2.

3. Life cycle How an animal starts life, grows to be an adult, has young and dies.

4. White-tail deer  The baby deer is called Fawn  The fawn drinks Milk from its mother to grow up  The fawn looks like its mother

5. White-tail deer  The fawn grows up to a yearling  The young deer is called Yearling  The yearling also looks like its mother

6. White-tail deer  The yearling grows up to an Adult deer