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Neuroscience > Advanced Scientific Skills > Flashcards

Advanced Scientific Skills Flashcards

1
Q

Dissociation constant (Kd) equals:

A

k2/k1
OR

[R][L] /[RL]

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2
Q

A lower Kd represents

A

Higher affinity of ligand for receptor

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3
Q

Bmax is:

A

Total concentration of receptors

[R] + [RL*]

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4
Q

Non-specific binding demonstrates:

A

A linear increase in [RL] with [L]

Radioligand binds to aspects of the experiment such as test tubes

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5
Q

How is radioligand binding measured?

A

Filter to trap bound radioligands

Estimate bound radioligands using liquid scintillation counter

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6
Q

How to calculate non-specific binding

A

Addition of significant excess of competitive ligand to displace radioligand

Remaining quantified radioligand binding is non-specific

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7
Q

Scatchard plot equation

A

[RL][L]= -[RL*]/ Kd + (Bmax/Kd)

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8
Q

Y axis of scatchard plot

A

Specific Binding/Total Ligand concentration

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9
Q

X Axis of scatchard plot

A

Specific ligand binding

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10
Q

Why is total ligand concentration used as free ligand conc

A

As in reality, bound ligand is very small

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11
Q

What produces a curved scatchard plot

A

Heterogenous binding e.g. cooperative binding

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12
Q

A high-affinity binding site in cooperative binding would produce

A

A low Kd with a steep gradient graph

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13
Q

A low affinity binding site would produce

A

A high Kd with shallow gradient graph

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14
Q

Negative co-operation

A

Kd less than the average Kd

Due to a decrease in affinity

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15
Q

Positive co-operation

A

Kd more than the overall Kd

Due to an increase in affinity

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16
Q

Hill Equation

A

log{B/(Bmax-B)} = nlog[L*] - nlogKd

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17
Q

What does n represent in the Hill equation/plot, and how to calculate this?

A

n is coefficient of how many ligands may bind a single receptor- the gradient of the line

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18
Q

How to calculate Kd from a Hill plot

A

X intercept is nlogKd

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19
Q

X axis of Hill plot

A

log Free (nM)

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20
Q

Y axis of Hill plot

A

log (B/Bmax-B)

21
Q

What is the IC50 in an indirect competition binding assay

A

Concentration of unlabelled ligand that inhibits 50% of radioligand binding

22
Q

What does the Cheng-Prusoff equation represent

A

Dissociation constant for unlabelled ligand

Ki= IC50/ (1+ [L*]/Kd)

23
Q

GPCRs and affinity

A

G-protein is coupled with GDP bound (to alpha subunit)
High affinity for Beta-gamma subunit

Activation dissociates alpha from beta-gamma, and GTP replaces GDP

GTP is hydrolysed back into GDP, increasing the alpha subunit affinity for beta-gamma allowing receptor coupling

24
Q

GTPyS or Gpp(NH)p and activation/affinity

A

Cannot be hydrolysed so subunits cannot reassociate; means ligand affinity is reduced

25
Q

What does a low IC50 represent

A

A low Kd so higher affinity

Left shift of competition binding curve

26
Q

What does a high IC50 represent

A

A high Kd so lower affinity

Right shift of competition binding curve

27
Q

Bigger negative log unlabelled indicates

A

A smaller concentration (to left of graph)

So a left shift indicates increased affinity at lower concs

28
Q

Accidental errors

A

Random in occurrence/magnitude
Normally distributed, measured by standard dev

Include measurement errors etc.

29
Q

Systematic errors

A

Arise from experimenter/equipment e
E.g. calibration errors

Minimise with calibration standards etc

30
Q

Positive controls

A

Demonstrate effect with a known effector

Done concurrently with negative control to assume appropriate protocol followed

31
Q

Negative controls

A

Demonstrate the repsonse with no effect

Done concurrently with positive control to assume appropriate protocol followed

32
Q

Reagent controls

A

e.g. blank used in spectroscopy

Solvent in which test substance is dissolved on its own

33
Q

Method controls

A

Adding a fixed amount of known internal standard to something being measured to assess reproducibility of a procedure

34
Q

Purpose of student’s t test, and what it represents

A

Determine if the means of two groups are statistically significant

Assumes a normal distribution

T value represents ratio of ‘signal’ (variance between groups) to ‘noise’ (variance within groups)

35
Q

Types of t test

A

Unpaired T Test
- For two independent groups

Paired T Test
- Two non-independent groups

36
Q

Interpreting T test

A

T Value compared to t-table

T value lower than critical value proves the null hypothesis

37
Q

H0 is

A

Null hypothesis (no significant difference)

38
Q

ANOVA (Analysis of Variance) + Post Hoc tests

A

T-test for multiple groups

Post hoc test follows up significantly significant ANOVA result

39
Q

Bonferroni post-hoc test

A

P-significant value/number of tests

40
Q

Tukey’s Honestly Significant Difference post hoc test

A

Commonly used if ANOVA assumptions are met

41
Q

Chi Squared Test purpose

A

Analysis of binary data/discrete variables

42
Q

Chi squared value

A

Sum of {(O-E)^2}/E

O is observed value
E is expected value

43
Q

Null hypothesis (H0) rejected

A

if greater than probability listed at p=0.05

44
Q

how to calculate expected value in Chi squared

A

Total receiving exposure x (Number with outcome/total patients)

45
Q

Type 1 (alpha) error

A

Significance test asserts H0 is false, but actually true

46
Q

Type 2 (beta) error

A

Significance test asserts H0 is true, but actually false

47
Q

Calculation of sample size

A

Requires a power calculation based on probabilities of Type 1 and 2 errors occuring

48
Q

What is power, typical value

A

Probability of detecting a true difference with a particular sample size

80-90% is normally considered reasonable

Neuroscience (17 decks)

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