1 October 2008Copyright: Ganesha Associates 2008 1 Basic reading, writing and informatics skills for biomedical research Segment 5. Developing testable.

1 October 2008 Copyright: Ganesha Associates 2008

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Basic reading, writing and informatics skills for biomedical

researchSegment 5. Developing testable

hypotheses


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The short version

• Student projects tend to fall into three categories– No hypothesis, i.e. observational– Weak hypothesis– Strong hypothesis

• The work is likely to be published in a – National journal– Low impact factor journal– High impact factor journal


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Coin-tossing - an example

• I wonder how many heads or tails I will get if I toss this coin 100 times– No model

• The frequency distribution of heads and tails will be approximated by a binomial distribution with n=100 and p=0.5– Simple model, based on symmetry

• A detailed analysis of the dynamics reveals that the probability of a head is 0.51– Complex model, based on asymmetry


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Coin-tossing – impact on CV

• None, or possibly negative• R. A. Fisher and others did perform this

experiment in the early days of biological statistics, before the advent of computers, as a proof that the bionomial distribution tended towards a normal one at high levels of n.– Interestingly they all found that p was usually slightly

higher than 0.5, but ignored this.

• Persi Diacusis, Susan Holmes and Richard Montgomery (Stanford, 2004) publish a paper on the ‘Dynamical bias in the coin toss’


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Coin tossing - relevance

• I think that there will be a correlation (+ or -) beween mutations in gene x and susceptibility to disease y– No causal relationship established

• I predict that mutations in gene x will increase susceptibility to disease y because patients with disease y often have low levels of gene product x.– Built-in control, patients with normal levels of the gene product should

not have the disease.

• I predict that chemically non-neutral mutations in gene x will increase susceptibility to disease y in patients with low levels of gene product x.– Second level of control – neural mutations should by asymptomatic


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Coin-tossing – morale of the story

• With a strong hypothesis, you:– Avoid following leads which go nowhere –

false positives, fail early– Avoid ignoring unexpected observations that

are of high interest – false negatives– May need to do less work !– May get published in better journals !


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The scientific method

• The steps necessary for scientific investigation:– the observation of phenomena,– the formulation of a hypothesis concerning the

phenomena,– the development of protocols to test the

validity of the hypothesis,– experimentation– a conclusion that supports or modifies the

hypothesis


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‘What’ comes before ‘how’

• Science begins with observations

• However, observations are rarely enough to warrant publication

• Exceptions ?– New technology, imaging, etc– Unusual clinical case history– Discovery of a new species– Description of an ecosystem


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No hypothesis, no science ?

• Taxonomy: The naming and assignment of organisms to taxa

• Systematics: The area of biology that deals with the diversity of living organisms, their relationships to each other through evolution, and their classification.

• Ecology: The study of how organisms interact with each other and their physical environment

• Clinical case study: An uncontrolled observational study involving an intervention and outcome in a single patient


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Only exceptional exceptions

• New technology, imaging, etc– New insights into how processes work

• Unusual clinical case history– New insights into disease mechanisms

• Discovery of a new species– New genera, schemes of classification

• Description of an ecosystem– New understanding of underlying mechanisms


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What is a hypothesis ?

• A prediction about how something works• Strong: A testable idea that can be proved

right or wrong with experiments • This prediction can be falsified but not

verified absolutely since there will always be a possibility that there is an alternative reason for the results


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What is a hypothesis ?

• A strong hypothesis is based on a series of premises – things that are already known with some certainty

• Each premise must be supported by references back to the (international) primary literature

• So a strong hypothesis will be backed by references to recent papers in high quality journals


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Testing a hypothesis - 1

• The first stage of any scientific analysis is to state the null hypothesis that is to be tested.

• This states that if we observe changes in the system or thing we are observing, that they are not significant, or were not caused by anything we did.

• The null hypothesis is denoted symbolically as H0.

• For our example, the null hypothesis could be that “there is no difference in precipitation levels between urban and adjacent rural areas”.


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• It is also necessary to state the alternative hypothesis (H1) – that there is an increase in precipitation levels in urban areas relative to adjacent rural areas because of the heating differences of the two surface types (the urban area heats up more and has increased convective uplift).

• Notice, it is a lot easier to specify the H0 version. H1 requires an understanding of convection, thermodynamics and so forth.



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• The H0 hypothesis protects us from trying to explain results that have no significance.

• The H1 hypothesis challenges us to make sure we have thought of all of the other factors that could cause the effects we observe and excluded them by appropriate experimental design or via additional experiments.



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• You can often spot problems with project design by analyzing the Introduction to the proposal.

• If you edit out repetitive statements and non-essential background information, you should be left with a logical sequence of statements which leads to a clear H1 hypothesis.

• Unlike H0 hypotheses – there is no treatment effect – you have to have a mechanism in mind in order to formulate the H1 hypothesis.

• Without this you have no logical structure to connect your results back to a known process or mechanisms.



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• For example, this is the edited version of the introduction to a scientific paper. Other than remove a couple of repetitious statements, I have made no changes.

• 1. Ectomycorrhizal fungi (EMF) have a fundamental role in nutrient absorption of many plant species.

• 2. Tree species of ecological and economic relevance in reforestation programs depend on ectomycorrhizal symbiosis, especially in soils contaminated by mining activities.

• 3. The ability of EMF to reduce the toxicity of heavy metal ions (e.g. copper) in their host plants is accompanied by the decrease of metal concentrations in the aerial part of the plant.

• 4. Due to increased absorption of these metals by the EM roots and the accumulation in the extra radical mycelium, greater tolerance to such elements is achieved by the host.

• 5. Research has been conducted to determine the sensitivity of EMF to a variety of potentially toxic metals to understand the diverse mechanisms through which the fungi may tolerate heavy metals.

• 6. Enzymatic activity is important for the mobilization and transference of soil nutrients through EM fungi towards the host plant.

• 7. In this study we investigate the effects of copper and phosphorus concentrations on mycelial growth and enzymatic activities of the EM fungi Pisolithus microcarpus, Chondrogaster angustisporus and Suillus sp. in two growth experiments.



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• The logical discontinuity occurs between statements 6 and 7. Since copper is toxic and phosphorous a fertilizer, we are almost certainly going to see effects. But what do they mean ?

• There is actually quite a large literature on copper toxicity in plants. Several mechanisms have been identified and it would have been possible by choosing the experimental conditions carefully to distinguish which ones were operating under this particular set of experimental conditions.

• Hence the introduction should have continued after point 6 to develop reasons for a more selective approach. This would form the basis for the missing H1 hypothesis.



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Hummingbird territorial behaviour


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H0: Hummingbirds are randomly distributed in space and time.

Most hummingbird species demonstrate strong territorial behavior

If a bluffing charge attack does not work, the residentmay engage the trespasser in a brief but intense physical battle

So why do hummingbirds defend territories ?



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H1

If territory = F(energy), then behavior not species-dependent

If territory = F(advertisement), then behavior species and sex dependent

If…

If…


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Territorial behaviour in 1971

• Time, Energy, and Territoriality of the Anna Hummingbird (Calypte anna) Science 173 (1971) 818-821.

• The male Anna Hummingbird accommodates seasonal changes in energy demands by varying its allocation of time and energy among different activities; total energy expenditures change relatively little.

• Augmented territorial defense during the breeding season is made possible by increased feeding efficiency due to the availability at this time of very nectar-rich flowers.


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Hummingbird territoriality since• Digestive physiology is a determinant of foraging

bout frequency in hummingbirds. Nature. 1986 Mar 6-12;320(6057):62-3.

• Mitochondrial respiration in hummingbird flight muscles. Proc Natl Acad Sci U S A. 1991 Jun 1;88(11):4870-3.

• Cloning and analysis of the gene encoding hummingbird proinsulin. Gen Comp Endocrinol. 1993 Jul;91(1):25-30.

• Flight and size constraints: hovering performance of large hummingbirds under maximal loading. J Exp Biol. 1997 Nov;200(Pt 21):2757-63.


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Hummingbird territoriality since

• Hovering performance of hummingbirds in hyperoxic gas mixtures. J Exp Biol. 2001 Jun;204(Pt 11):2021-7.

• Adipose energy stores, physical work, and the metabolic syndrome: lessons from hummingbirds. Nutr J. 2005 Dec 13;4:36.

• Neural specialization for hovering in hummingbirds: hypertrophy of the pretectal nucleus Lentiformis mesencephali. J Comp Neurol. 2007 Jan 10;500(2):211-21.

• Three-dimensional kinematics of hummingbird flight. J Exp Biol. 2007 Jul;210(Pt 13):2368-82.


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Another example: Alzheimer’s Disease

• There are several distinct hypotheses about the origins of AD

• You can find out more at this web site: http://www.alzforum.org/res/adh/cur/knowntheamyloidcascade.asp .

• They include:– Chronic Stress Hypothesis of AD– Axonal Transport Dysfunction Hypothesis– The Amyloid Cascade Hypothesis

http://www.alzforum.org/res/adh/cur/knowntheamyloidcascade.asp

http://www.alzforum.org/res/adh/cur/knowntheamyloidcascade.asp


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Alzheimer’s Disease - Amyloid Cascade Hypothesis


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Scientific frontiers


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Hypothesis learning points

• Successive hypotheses build directly onto previous work

• So they need to become technically more sophisticated over time moving from the general to the particular

• A given problem can be associated with a number of very different hypotheses – your experiments should include tests to exclude these alternative explanations


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Hypothesis learning points

• Hypotheses can be weak (observational) or strong (mechanism-based)

• For example, a hypothesis which predicts that a tossed coin will end up ‘heads’ 50% of the time is much weaker than one that can predict the exact sequence of ‘heads’ and ‘tails’

• So hypothesis ‘quality’ is important too


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Hypotheses, problems with

• You can only formulate an hypothesis if you have a clear conception of how something might work

• Your hypothesis will only be of interest to the scientific community if it leads to new knowledge that is considered valuable

• So you must be up-to-date at all times• In addition, unlike physics or chemistry, biology

still contains many unknowns• So building hypotheses and testing them is very

difficult


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Case Study One

– Observations• There is evidence that the central nervous system can influence bone

metabolism• Neurotransmitter, e.g. serotonin, receptors are found bone• Drugs that inhibit specific neurotransmitter actions can affect bone growth in

human– Hypothesis

• If serotonin plays a role in regulating bone growth, then reducing serotonin release in bone will slow growth

– Experiment• Inject mice with drugs (SSRI’s) that have a profound effect on serotonin

metabolism and measure impact on growth of femur over time– Result

• Small reduction in bone growth observed– Referees comments

• Is this a direct or an indirect effect ?


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Case Study Two

– Observations• A plant extract (E) is used to treat diabetes• Prenatal malnutrition may cause diabetes

– Hypothesis• If E plays a role in regulating blood sugar levels then the responses

to E will be affected by dietary history

– Experiment• Measure acute and chronic effects of E on glucose and insulin

levels in normal and prenatal malnourished rats fed either on a standard or high glucose diet

– Result• E does appear to reduce blood sugar levels

– Referees comments• Statistical complexity of experimental design prevents any clear

conclusions being drawn about mechanism


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Case Study Three

– Observation• Fungal and other microbial symbionts can improve nutrient uptake

by plant roots

– Hypothesis• Soil microbial diversity is adversely affected by conventional farming

techniques

– Experiment• Compare microbial diversity associated with root soil in vines

cultivated using either conventional or organic techniques

– Result• Diversity and metabolic vigour higher in soils associated with the

roots of organically cultivated plants

– Referees comments• What was the control for this experiment ? Maybe the differences in

the two soil areas has nothing to do with agricultural methods.


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Case Study Four

– Observation• A patient suffers from an unusually aggressive form of

retinoblastoma– Premise

• Patients who develop retinoblastoma also have a particular type of genetic defect which can be identified cytogenetically

– Hypothesis• This patient may also show an unusual cytogenetic pattern which

could be useful diagnostically– Result

• The patient does indeed have a unique cytogenetic profile, but there are many differences from the pattern normally seen in retinoblastoma cases

– Referees comments• There are several alternative hypotheses which could explain these

results


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Case Study Five

– Observation• Infection by certain human papilloma virus serotypes can lead to

cervical cancer. One study has shown that the prevalence of HPV 31 and 33 is much higher in Recife than elsewhere in Brasil

• Mutations to human P53 are often associated with the more severe consequences of HPV infection

– Hypothesis• There is a strong correlation between patients with advanced HPV

31 and 33 disease and a new, as yet undescribed p53 mutation which is found mainly in the NE of Brasil

– Result• There is a strong correlation between patients with HPV 31 and 33

infections, cervical cancer and P53 mutations

– Referees comments• There is no firm evidence that the correlation has a genetics basis


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Hypotheses, more problems with

• These five hypotheses failed • Either because they were not based on a rigorously

researched mechanism of action • Or because the experimental design was weak• As a consequence, important variables were not

controlled for• And the results could not be explained within the context

of the model• Moral: Hypotheses are often wrong first time around• Strong hypotheses usually require less work to prove

than weak ones !


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Para crescer, não deixe de ler

– Science is about discovering new things– And the frontiers move fast– So if you want to keep up– You need to read– In English– Every day

– Good luck!


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Practical activity 5 - Hypotheses

• Use a recent review article to select an important problem in an area that is outside your chosen field of study.

• Find out what progress has been made subsequently to solve this problem.

• What hypotheses were made and how were they tested ?• Make a 5-slide presentation describing this progress to the

group.• You will be judged according to:

– The clarity of your presentation style– The clarity of the scientific advances made– Your analysis of what the next steps to be taken should be (the new

hypotheses)

1 October 2008Copyright: Ganesha Associates 2008 1 Basic reading, writing and informatics skills for biomedical research Segment 5. Developing testable.

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