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Writing is Important!. Recommended reading: Clean, Well-lighted Sentences: A Guide to Avoiding the Most Common Errors in Grammar and Punctuation by Janis Bell. Writing is Important!. Recommended reading: Eats Shoots and Leaves: The Zero Tolerance Approach to Punctuation by Lynne Truss.

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writing is important
Writing is Important!
  • Recommended reading:

Clean, Well-lighted Sentences: A Guide to Avoiding the Most Common Errors in Grammar and Punctuation

by Janis Bell

writing is important2
Writing is Important!
  • Recommended reading:

Eats Shoots and Leaves: The Zero Tolerance Approach to Punctuation

by Lynne Truss

biology lab background iii properties of light

Biology Lab Background III / Properties of Light

September 15, 2008

Overview of Microscopy

Dr. Behonick

topics for today
Topics for today …
  • Biology Lab Background III
    • Experimental Design
    • Types of Data
  • Properties of Light
the scientific method
The Scientific Method

Make

Observation(s)

from http://asweknowit.net/MIDDLE_SCH/DWA_7_scientific_method.htm

types of experiments
Types of experiments
  • in vitro
    • “within the glass”
    • performed outside a living organism in a controlled environment (ex = in a test tube)
  • in vivo
    • “within the living”
    • performed in/on living tissue of intact organism
  • ex vivo
    • “out of the living”
    • performed in/on living tissue in artificial environment outside organism from which it was harvested (ex = cell culture)
  • in silico
    • performed entirely on computer or by computer simulation
variables
Variables
  • variable = what is measured or manipulated in an experiment
    • independent variable = variable you have control over, what you can choose and manipulate (value(s) you are manipulating, also known as “manipulated variable”)
    • dependent variable = what you measure in experiment (what is affected during experiment, responds to independent variable)
examples
Examples
  • effect of different doses of a drug (IV) on severity of disease symptoms (DV)
  • effect of different quantities of fertilizer (IV) on how your house plants grow (DV)
    • would want to control other variables like water, soil, size of pot, time in sun, etc.
  • effect of different water temperatures (IV) on how fast a sugar cube will dissolve (DV)
  • effect of paper towel brand (IV) on how much water can be soaked up with one paper towel sheet
cause effect
Cause & Effect

change in

dependent variable

(effect)

manipulation of

independent variable

(cause)

controlling for bias
Controlling for Bias
  • blindedness - controlling for conscious/unconscious bias in research
    • placebo effect = subject receiving placebo reports change in symptoms (despite lack of actual chemical treatment) due to expectation or belief that it will work
    • observer bias = error in observation/ measurement when observers overemphasize behaviors they expect to find & fail to notice behavior they don’t expect
controlling for bias12
Controlling for Bias
  • single-blind study = subjects are blinded but experimenters are not
    • ex = subject does not know whether receiving drug or sugar pill
    • experimentor either can’t be blinded due to design of study or doesn’t need to be because can’t introduce further bias
  • double-blind study = both subjects and experimenters are blinded
    • subjects randomly assigned to groups, experimenters don’t know assignments
    • master list of group assignments kept by third party until experiment finished
  • “triple-blind” study = double-blind study in which person interpreting results is also blinded (ex = statistician)
what is enough proof
What is enough proof?
  • statistical analyses
    • looking for patterns in your data after accounting for randomness/uncertainty and using this information to draw inferences about process/population being studied
    • are these results a big enough deal for me to care?
    • are these results due to random chance?
    • are these results generalizable?
what is enough proof14
What is enough proof?
  • sample size = # of observations (or pieces of collected data) that constitute a result
    • ex = # of subjects per group in experiment
    • if you’re trying to make a general statement about a population, bigger sample size  more precise statement
controls
Controls!
  • internal proof for your experiment
  • negative control - shows that a negative result is possible in your system
  • positive control - shows that a positive result is possible in your system
  • “What else could have caused observed effect?”
baking bread a tale of good controls17
Baking bread: a tale of good controls
  • does yeast Dani found in the back of the freezer still work?
  • experimental design
    • controls
baking bread a tale of good controls18
Baking bread: a tale of good controls

negative control

positive control

shows a negative

result is possible

shows a positive

result is possible

baking bread a tale of good controls19
Baking bread: a tale of good controls

negative result

positive result

slide21
NOTE
  • datum = singular
    • a single measurement, result, etc.
  • data = plural
    • a collection of measurements, results, etc.
types of data22
Types of Data
  • quantitative data - numerical data
    • scale of measurement has magnitude (some things are bigger than others)
    • ex - height, cholesterol level
  • qualitative data - not numerical data, may be categorical or descriptive
    • scale of measurement is a set of unordered categories
    • ex - types of trees, types of compounds
quantitative data
Quantitative Data
  • described in terms of numerical quantity
    • discrete data - there are only a finite # of values possible & values can’t be subdivided and still be meaningful (ex - population data)
    • continuous data - data that can be measured on a continuum (physical measurements are generally this type of data); can have almost any # value and be subdivided and still be meaningful
  • can be displayed in charts, tables, graphs, histograms
  • can be analyzed using statistics
qualitative data
Qualitative Data
  • described on basis of relative characteristics
    • color
    • shape
    • texture
    • temperature
    • odor
    • taste (generally not used in research science)
  • sometimes considered “less valuable” by research scientists
example 1
Example 1

Qualitative data - pirates carry parrots

while ninjas do not.

example 126
Example 1

Quantitative data - there are 6 pirates

& 2 ninjas.

example 2
Example 2
  • hot fudge sundae
    • qualitative data
      • cold to touch
      • creamy texture
      • serving glass is colorless & transparent
    • quantitative data
      • serving temperature is -10oC
      • serving glass is 6 inches in height
      • cost $6.95
microscopy data
Microscopy Data
  • microscopists collect both qualitative & quantitative data
    • qualitative data
      • color of specimen
      • overall structure of specimen
      • shape of cells
      • type of cells present & their location
    • quantitative data
      • how much bigger is one specimen (or one particilar region of a specimen) vs. another?
      • how many cells are in one part of a specimen vs. another?
data collection
Data Collection
  • accuracy = closeness of measured value to a standard value. accuracy is independent of precision.
    • ex - if in lab you obtain a weight measurement of 3.2 kg for a given substance, but known weight is 10 kg, then your measurement is not accurate (not close to known value)
  • precision = the closeness of 2 or more measurements to each other. precision is independent of accuracy.
    • ex = if you weigh 10 kg substance 5 times & get 3.2 kg each time, then your measurement is very precise but not accurate.
light
Light
  • travels @ 186,000 miles/sec
    • ≈ 669,600,000 miles/hour
  • can think of light as
    • stream of tiny particles/energy packets (photons)
    • a wave (light waves)
      • we’ll stick with this interpretation
the thing about waves
The thing about waves …
  • they’re made up of energy, not matter
    • at the beach
    • at the laundromat
measuring waves
Measuring Waves
  • period (T) = time to one complete wave cycle
  • frequency () = # periods per unit time; measured in Hz
    • ex = # waves that pass a particular point in space during specific time interval
  • wavelength (l) = distance between same point on 2 sequential waves (ie - 2 sequential peaks, 2 sequential troughs)
  • amplitude (A) = maximum distance from highest point of peak to equilibrium in 1 wave cycle

A

amount of time required

to complete = T

the thing about waves38
The thing about waves …
  • they’re made up of energy, not matter
    • at the beach
    • at the laundromat
  • light waves ~ water waves but don’t need medium to travel thru
    • can move thru medium or vacuum
      • fastest in vacuum, slow down in medium
    • energy in light waves = electrical & magnetic fields
      •  light = electromagnetic radiation
em spectrum

1 m

106 nm

106 nm

10–5 nm

1 nm

10–3 nm

103 nm

103 m

Micro-

waves

Radio

waves

Gamma

rays

X-rays

UV

Infrared

Visible light

380

450

500

550

600

650

700

750 nm

Shorter wavelength

Longer wavelength

Lower energy

Higher energy

EM Spectrum

wavelengths 400 – 700 nm constitute visible light for humans

higher frequency

lower frequency

em resources
EM Resources
  • EM Wave Propagation Tutorial

http://micro.magnet.fsu.edu/primer/java/electromagnetic/index.html

  • Basic EM Wave Properties Tutorial

http://micro.magnet.fsu.edu/primer/java/wavebasics/index.html

slide43

Microscopy Techniques

objective

light source

transmitted

bright field

phase

DIC

transmitted light

objective

light source

Transmitted Light
  • amplitude object = pigmented or stained sample
    • ex = histology specimens
    • seen w/ brightfield microscopy
  • phase object
    • ex = most biological samples
    • seen w/ phase or DIC microscopy
slide45

Objects and transmitted light

light wave

amplitude object

seen as color

phase object

not seen

contrast
Contrast
  • contrast = difference in color & light between parts of an object/image
    • requred to see an object by microscope
    • can come from variations in
      • intensity (DIC, phase)
      • color (bright field, fluorescence)
contrast47
Contrast
  • cells typically are
    • transparent (not amplitude objects)
    • phase objects
    • low in contrast
  • contrast-generating techniques turn phase differences into intensity differences so we can see unstained cells using transmitted light
    • ex = DIC microscopy
refraction
Refraction
  • refraction = bending of light when it passes from a medium of one density into a medium of another density
    • light travels at different speeds through different media (ex = air, water, glass)
slide51

Microscopy Techniques

objective

light source

“transmitted”

slide52

Microscopy Techniques

light source/objective

reflected

dissecting microscope

slide53

Microscopy Techniques

light source/objective

reflected

dissecting microscope

slide54

Microscopy Techniques

light source/objective

incident/epi-illumination

fluorescent

slide55

Microscopy Techniques

light source/objective

incident/epi-illumination

fluorescent

atoms
Atoms
  • smallest units of chemical elements
  • composed of protons, neutrons & electrons
    • protons & neutrons make up nucleus
    • electrons live in shells outside nucleus
  • atomic # = # of protons
electron configurations
Electron Configurations

Helium

2He

Hydrogen

1H

2

He

4.00

Atomic number

Atomic mass

Element symbol

First

shell

Electron-shell

diagram

Lithium

3Li

Beryllium

4Be

Boron

5B

Carbon

6C

Nitrogen

7N

Oxygen

8O

Fluorine

9F

Neon

10Ne

Second

shell

Sodium

11Na

Magnesium

12Mg

Aluminum

12Al

Silicon

14Si

Phosphorus

15P

Sulfur

16S

Chlorine

17Cl

Argon

18Ar

Third

shell

slide59

(8 e-)

Figure 2.8 Energy levels of an atom’s electrons

(8 e-)

(2 e-)

absorption emission
Absorption & Emission
  • absorption = electrons of atoms of a substance can absorb energy from external sources including light
    • electrons become “excited”
  • emission = electron falls back to original “de-excited” state, releasing EM radiation
absorption emission61
Absorption & Emission
  • fluorescence microscopy
    • fluorophore = molecule that upon absorbing energy can reach excited state, then emit energy
    • microscope light source irradiates sample w/ specific wavelength of light
    • light absorbed by fluorophores in sample
      • causes electrons in fluorophores to become “excited” & move up a level temporarily
      • when these temporarily excited electrons fall back to their original state, they emit their own light energy, which is the fluorescence you see under the microscope
fluorescence
Fluorescence
  • fluorescence = process of excitation, loss of energy & emission of light from a fluorophore
resources
Resources
  • Electron Excitation & Emission Tutorial

http://micro.magnet.fsu.edu/primer/java/fluorescence/exciteemit/index.html

  • Invitrogen Fluorescence Tutorial

http://www.invitrogen.com/site/us/en/home/support/Tutorials.html.html?CID=fl-GA-FluorTutorial

  • Invitrogen Fluorescence SpectraViewer

http://www.invitrogen.com/site/us/en/home/support/Research-Tools/Fluorescence-SpectraViewer.html

references
References
  • Abromowitz, M., Parry-Hill, M.J., Fellers, T.J., Davidson, M.W. “Physics of Light and Color.” Molecular Expressions Optical Microscopy Primer. Olympus America, Inc. & Florida State University. 14 September 2008 <http://micro.magnet.fsu.edu/primer/lightandcolor/electromaghome.html>.
  • “Fluorescence Tutorials: Introduction.” Invitrogen Tutorials. Invitrogen Corporation. 15 September 2008 <http://www.invitrogen.com/site/us/en/home/support/Tutorials.html.html?CID=fl-GA-FluorTutorial>
  • Freudenrich, C. “How Light Works.” How Stuff Works. Discovery Communications, Inc. 14 September 2008 <http://science.howstuffworks.com/light.htm>.
  • Giorgi, G. “Intro to Microscopy.” Merritt College Biology 035, 24 January 2008.
  • Shanoski, J. “Introduction to Electromagnetic Radiation and Optics.” Merritt College Biology 035, 12 February 2008.
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