Forensic science

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Keele University Internship

“Forensic science”

Entomology:

Changes in hydrocarbon profile of

outdoor Calliphora vicina puparial

cases

2 0 . 0 0_{2 1 . 0 0} 2 2 . 0 0 _{2 3 . 0 0} 2 4 . 0 0 2 5 . 0 0 _{2 6 . 0 0} 2 7 . 0 0 _{2 8 . 0 0} 2 9 . 0 0 3 0 . 0 0 _{3 1 . 0 0} 5 0 0 0 0_{0 0} 1 e + 07 1 . 5 e +_{0 7} 2 e + 07 2 . 5 e +_{0 7} T i m e - - > A b u n d_{a n c e} T I C : W k 2 P C 7_{. D \ d a t a} . m s

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Avans University Breda Forensic Chemistry Science Internship Keele University

Analysis of hydrocarbons on blowflies

Student information:

Name: Deen van Logchem

E-mail address: d.vanlogchem@student.avans.nl

Student number: 2013234 Telephone number:0031624980099 (NL) Supervisor information:

Keele University

Name: Prof. F. Drijfhout

E-mail address: f.drijfhout@chem.keele.ac.uk

Keele University

Name: Hannah Moore (PhD)

E-mail address: h.e.moore@epsam.keele.ac.uk Avans University Breda

Name: Mr. Henk Haarman E-mail address: hf.haarman@avans.nl

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Summary

Forensic entomology is the branch of forensic science which focuses on insects, and in this study the hydrocarbons on the cuticle (CHC) of the insects. The

hydrocarbons (HC) are on the insects cuticle as a function to prevent dehydration of the insect. Also some studies concluded that the hydrocarbons work as a recognition system in ant colonies. During the growth and subsequently the ageing of the larvae, pupae and adult fly, the hydrocarbon-profile on the cuticle changes over time, but also hydrocarbons are found in the puparial cases after hatching. The species used for getting eggs and larvae for analysis were

microscopically identified on fly characteristics. Changes of alkanes with chain length of C17-C35 are found in different combinations in the life cycle. The rearing conditions used for the analyses of larvae seem to have an effect on size and behaviour but the CHC-profile seems really stable for aging the larvae. For this reason the analysis of CHC-profile on larvae seem a good tool to age the larvae, which can be of great importance in forensic aspects.

To plot the results from 10 repeats on every time interval, the peak areas of the hydrocarbons from the chromatograms were put into excel. When the areas of all the compounds were gathered, a principal component analysis (PCA) calculation is done on these results to reduce the amount of data. After PCA these results are plotted and the differences or similarities in HC profile at the time intervals can be seen. The vaporation/degradation of hydrocarbons in the puparial cases

exposed to outside conditions, seem to have a similar degradation pattern as the puparial cases from inside conditions, but temperature seems to play a role in the speed of changes in the empty puparial. PCA can be used in different projects and to give an example; the food competition experiment from the first 4,5 months of the internship is reanalysed with PCA and bigger changes can be seen in hydrocarbon profile in larval stages.

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Introduction

The establishing of the post mortem interval (PMI) can be a very important in solving forensic cases that involve a unknown cause of death. This is where forensic entomology comes in, the forensic entomology uses insects found on corpses and the surroundings of the corps to determine a window of time that the body has been exposed to the outdoors. Forensic entomology is not recognized in all countries and the research to determine a PMI is very hard. More research is necessary to strengthen the findings of this specialization within the forensics. This is where research on hydrocarbons on the cuticle (CHC) of insects can be helpful. This research could be a promising tool to estimate the PMI or

strengthen it. The hydrocarbons are analyzed on a GC-MS and the samples used, are from different life stages of the larvae of blowflies.

The second part of the internship at Keele University focused more on a own project. This project is at the same time my graduation project which is also presented before graduation and more focused on the chemistry of this research. The project focuses on the effect of outside conditions on degradation of

hydrocarbons in puparial cases. The hydrocarbon profile left in the puparial case are the same of a new hatched adult fly, this profile is expected not to have new compounds appearing but as mentioned before the degradation of the present hydrocarbons over time can show the amount of time a puparial case is exposed to the outside (which gives an “age” of the puprial cases). Also previous results on a food competition experiment on feeding larvae will be looked in again for more chemistry focused analyses.

The report is divided in 9 chapters, chapter 1 contains a general view in gas-chromatography and mass spectrometry (GC-MS). In chapter 2 information about the different hydrocarbons can be found. Chapter 3 contains the different life stages of a blowfly. Chapter 4 gives a resemblance between hydrocarbons and the life stages of a fly and information about structures of hydrocarbons. Chapter 5 describes the methods used for all the to obtain the results gathered. In

chapter 6 the analysed results are shown from all the different steps taken to be able to draw conclusions, which can be found in chapter 7. And finally chapter 8 were improvements and possible future work on the projects can be found.

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1. Gas Chromatography – Mass Spectrometry

In spectrometry the mass spectrometer (MS) is a very strong tool that is used to identify unknown compounds and quantify known compounds. MS is a very sensitive system that can use separation techniques, such as chromatography, to analyze complex mixtures. To keep the high sensitivity the MS has different parts of the system that have to be optimized. The important parts of the MS are shortly explained in the text below.

1.1 Ion Source

The samples in the GC-Ms are introduced by the sample inlet, and then go into the Ion Source. As the name might subject the molecules that are introduced get ionized. This is necessary before the mass spectrometer can analyze a sample. A method (that is most commonly is used) to ionize and fragment a sample is to bombard the molecules with electrons. This results in different fragmentations patterns which can be used, by using software most commonly, to identify the sample compound.

The source of the electrons that bombard the molecules are the filament. A repeller is used to direct ions straight through a series of lenses in the ion source. Without all of these components, the molecules in the sample would not be ionized and they can’t reach the qaudrupole.

1.2 Quadrupole

After the molecule samples are ionized by the ion source, the sample molecule and it’s fragments enter the qaudrupole. The purpose of the quadrupole is to filter these molecules. It eliminates the ions that are unwanted, what only allows the selected masses to pass through the quadrupole. After the molecules leave the ion source it generally gets a +1 charge. Cause the quadrupole filters to a mass-to-charge ratio, and every molecule gets a +1 charge, it separates according to mass only. By changing the amplitude of the electric field of the quadrupole it controls which ions will make it through to the quadrupole to the detector. The amplitude is regulated by positive (DC) and negative rods (RF) in the qaudrupole. The ratio between the DC and RF amplitude gives the selectivity tot the qaudrupole. As mentioned above the unwanted or not attracted ions are pumped away by the vacuum system.

1.3 Detector

Once a ionized sample has been filtered by the mass-to-charge (m/z) ratio in the mass filter, the abundance must be detected and reported to the data system. A detector is used to collect and count ions, one ion at a given time, regardless to the kind of mass filter. Inside the detector, the ions generate a signal which can be displayed by the data system.

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1.4 Vacuum system

The ion source, mass filter and detector are in a vacuum. The vacuum system makes it possible for ions to move from the ion source to the detector without colliding with other ions, sample molecules, air and or water. This way the

vacuum gives a minimizing factor for collisions and insures that more ions of the sample will be counted by the detector [1,2].

2. Hydrocarbons

In this project hydrocarbons are used for estimating the age of different stages of the blowfly lifecycle which can be a useful tool for estimating the PMI in forensic entomology, but this research can’t be done without knowing the

characterization of these hydrocarbons. Hydrocarbons are compounds composed of only hydrogen and carbon atoms. Carbon atoms are unique in their ability to connect to each other in order to form molecular chains of length. Hydrocarbons can be split into different groups to identify certain molecular structures.

Important groups in insect hydrocarbon analyses are;

- Alkanes: hydrocarbon chains containing single bonds between carbon

atoms.

- Alkenes: hydrocarbon chains containing at least one double bond between

any two carbon atoms.

- Monomethyl alkanes: Hydrocarbon chains containing a single methyl group

- Dimethyl alkanes: Hydrocarbon chains containing two methyl groups

located at the carbons within the chain.

2.1 Hydrocarbon Structure

Hydrocarbons are compounds that consist long chains of carbons and hydrogen atoms. No other compounds will be found in a hydrocarbon structure. The basic structure of all hydrocarbons are the same but there can be some differences between them. As shown in figure 1

the difference between de

hydrocarbons are defined by the presence of double bonds.

Hydrocarbons also occur in their saturated and unsaturated state (olefins) and may have one or more methyl groups (CH3) attached to the chain. Hydrocarbons with a methyl attached in the chain is called a branched hydrocarbon. In the saturated form all of the carbons are single bonded. The unsaturated form has either

one (alkenes), two (alkadienes) or three (alkatrienes) double bonds at various

Figure 1: The structure of common hydrocarbon classes. These hydrocarbons are mainly found and the difference can be seen in the length of the chain, double bonds or methyl groups attached to the chain.

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positions of the long carbon chain. In addition, olefins can take the form of one of two isometric forms between the carbon atoms at the double bond in the

hydrocarbon chain. These are known as cis-alkenes (or Z-alkenes) and trans-alkenes (E-trans-alkenes), however all known hydrocarbons in insect are found in the Z-alkenes configuration.

The length of the hydrocarbons found on insect are between 19-35 carbon atoms long (C19-C35). However this number can be restricted by the technique that is used for the GC. Other high temperature columns might give longer hydrocarbon groups present on the cuticle of the insects.

2.2 Alkanes and Alkenes

The different kind of hydrocarbons analysed on the cuticle of insects give a different mass spectra. alkanes are characterised by high peaks of low ions in the mass spec. The intensity of the m/z at 41, 55, 71 an from here on decreasing peaks of the ions 85, 99, 113 etc. These ions are found in the mass spec of a alkane, the ions found are similar for each alkane so the amount of carbons in a hydrocarbon can only be identified by looking at the mass ion in the spectra. The mass ion is the ion that corresponds with the total mass of the hydrocarbon or alkane. Alkenes have a similar pattern in the mass spec, although the masses differ. Values of m/z 53, 69, 83 and 97 are present in high abundance followed by decreasing values of m/z 111, 125, 139 etc. The molecular ion in alkenes gives a higher abundance compared to the alkanes. The visual differences between the mass specs of a alkane and alkene can be found in figure 2. Note that an alkene has more distinctive mass ion and lower mass ions, also the v-shaped pattern (in red) of ion 69 in distinctive for a alkene.

Figure 2: Examples of an Alkane (A) and Alkene with mass spectra. The red line gives the difference in shape of the dominant peaks in the mass spectra.

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2.3 Branched alkanes

Monomethyl alkanes are very similar in mass spectra to the alkanes, except that the characteristic pattern is interrupted in the centre if the methyl group is located more or less on the middle carbon of the alkane chain. The pair of ions with increased abundance indicate the position of the methyl group on the linear chain as seen in figure 3. In this figure the spectrum of a 9MeC25 (9-methyl-pentacosene) is shown, where two ions are present. This pair on m/z 140:141 and 280:281 are formed after the compound is fragmented on the position were the branch is located. The ions shown in the middle of the spectra can be used to locate the position of the methyl group on the chain. In a case where the

branching of a methyl group is at the beginning of the hydrocarbon molecule, the spectra would like different and the increased abundance of ions will not be in the middle, but shifted to both edges of the spectra. One to the higher mass (close to the mass ion) and one at the beginning of the spectra (higher abundance region). The position of the methyl group on the molecule is a less stable bond then the hydrocarbon chain itself, for this reason due to the ion source (fragmention) the molecule will break easier on the bond were the methyl group is positioned. A similar pattern is found (seen in figure 3.d) with dimethylalkanes, but instead of each compound giving two additional characteristics ions in the spectra, now each compound yield four characteristic ion pairs. In monomethylalkanes the even ions are more abundant, but in dimethylalkanes, two of the ion pairs have a higher odd ion.

Figure 3: Examples of an monomethyl alkane (A) and a dimethyl Alkene with mass spectra. In the molecule the fragmentation of the molecule is shown with the serrated line. The created masses give a higher abundance cause the molecule breaks easier on the position where a methyl group is attached.

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2.4 Unknown hydrocarbons

Some mass spectra can be identified as an hydrocarbon but it can be really hard indentifying a branched hydrocarbon or mass spectra that are similar to an hydrocarbon. The main problem is that often two isomeric compounds, for

example 11MeC27 and 13MeC27 elute as a single peak. The mass spectra of this ‘single peak’ will therefore represent for both compounds and this means they can’t be separated by the GC-column. In this case the mass spectra will give a combination of both of these monomethyl alkanes and will be hard to identify separately. This is also one of the reasons why MS is way more powerful tool for complex compounds, cause in some cases the retention time of two compounds can be the same but the mass spec can be completely different, which makes the same peak a different compound.

Some hydrocarbons elute just before or between two alkanes, these

hydrocarbons can be branched or have different more complex structure which makes it hard to identify them. To get a good indetification on these compounds the retention index can be used [3,4,5,6,7,8,9].

2.5 Retention index

The retention index system is used for the purpose of substance identification in gas chromatography. The retention index is also known as the Kovats index, its a logarithmic sxale opn which the adjusted retention time of a peak is compared with those of unbranched/unknown alkanes.

Kovats (1958) created a system of indexing chromatographic retention properties of a stationary phase with respect to the retention characteristics of unbranched alkanes. These are used as reference materials since they are non-polar and soluble in most common stationary phases. The Kovats index, also I, for the unknown compound is calculated from the formula:

I=100 ∙

[

n+( N−n )

log

(

t

' r(unknown)

)

−

log

(

t

' r(n)

)

log

₍

t

' r(N)

)

−log

(

t

' r(n)

)

]

Where

n

is the number of carbonatoms in the smaller alkane,

N

is the number of carbonatoms in the larger alkane and t'

r is in all cases the adjusted

retention time. This definition makes the I (Kovats index) for a linear alkane equal to 100 times the number of carbon items in the molecule. For example a C18 alken will have a Kovats index of 1800. Because a C18 alkene will delute slightly before the alkane this value is estimated lower and around the value of 1790. In the paper of David A. Carlson 1998 (reference [...]) a elution pattern is made for methyl branced alkanes, where the retention indices are assigned to peaks, and then the patterns in GC peaks that contain homologs are marked to assist in GC-MS interpretation [8,9,10].

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2.6 Principal Component Analyses (PCA)

Principal component analysis (PCA) is a technique for reducing the amount of data when there is correlation present. Although it is not a useful technique if the variables are uncorrelated. Within this calculation there can be more ‘PC’s’, for example a PC1, PC2 etc. The difference between these calculations is that PC1 looks for the main components in the data file and their correlation/difference. So when there is a chromatogram with hydrocarbons the most present compounds are compared (the highest peaks). PC2 accounts for the next largest variation and so on. So when the focus is on more minor differences and therefore smaller peaks, then a higher ‘PC’ is used to calculate the correlation between these compounds. And not a PC1 because it looks at the correlation within the most present peaks which may not be as relevant.

The application in the project makes PCA useful because it makes a single data point for a single repeat from the 10 repeats on every time interval that is taken. The chromatogram (counts for one of the ten repeats) were interpreted using PCA as they can be hard to visualise in graphical form. This multivariate statistical technique groups data according to the statistically significant similarities among the chromatograms and helps to reveal any patterns or trends that might be present. It works by characterising a set of data by defining a small number of principal components, which are uncorrelated yet represent the significant variability within the dataset. This means that the inclusion of more principal components (PC’s) within the model includes features of decreasing significance. PCA is most successful where the variability within the dataset is described by a relatively small number of components.

3. Life cycle of blowflies

The blowflies have a life cycle which shows complete metamorphosis. This means that the different stages of the life cycle don’t look alike. It’s a complete

transformation from the eggs to larvae to adult fly. The cycle starts with an adult female fly who lay the eggs. The different life stages of a fly that are found on a corpse can help to make a possible prediction of the PMI.

3.1 The different life stages

The number of eggs laid by a fly is around 150-200, they are laid in batches and clumps and are placed on the corpse to provide good protection. The position where the eggs are laid need to contain enough food, and preferable moisterus. Therefore the fly will most likely lay the eggs in the mouth, nose and/or ears of the corpse. In a lifetime a fly lays around 2000-3000 eggs.

Figure 4: Blowfly pupae of varying ages. Note that the degree of darkening increases after time.

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The egg of an blowfly is usually bright white of colour, ranging in size from around 0.9 mm to over 1.5 mm long and 0.3-0.4 mm in wide. The outside of the egg is called chorion. The chorion can be reticulate or spotty. This sculpturing can be used, when investigated with a (electron) microscope, to identify a species which colonized a corpse. The

emergence of the first instar larva from the egg is called eclosion, although this term has also been used to describe any form of hatching. Therefore the three larval stages are known as 1st

instar, 2nd_{instar and 3}rd_{instar. There is}

another stage they go through before they pupate (which has different stages in colouring over time (figure 4)), called the post-feeding stage. At this point the maggots stop feeding and start

migrating away from the body seeking cool, dark and moistures conditions. From here on they emerge as adult flies and the cycle starts over (figure 5). The temperature has a influence on the hatching time of all

the stages, at a temperature around 21 to 24 degrees the hatching will be shorter then in colder circumstances. For forensic entomology the weather temperature is therefore an important factor to give a estimation of the PMI according to life stages. After the adult flies hatch from the pupae a empty puparial case is left behind. The puparial case still contains hydrocarbons left behind from the adult. The compound profile won’t change, but the concentration of the hydrocarbons left behind by the adult fly will decrease when the puparial case is exposed to the open-air [3,5,7,18, 20] .

3.2 Insect activity

During the bloat phase (putrefaction) insects become a major factor in the decomposition and modification of body tissues. Forensic entomologists learned that growth, feeding and migration are generally specific for each species and are effected by temperature, time of day and season as the changes of internal biochemical

decomposition. Blowflies are most likely to arrive first at a body who is

exposed to the outside (figure 6). They lay their eggs in shaded narrow

places, like the ears, nostrils, mouth, eyes

Figure 5: The life cycle of a fly. Notice the big transformation form egg to adult. The different stages can be used for identifying a species. Starting from the adult fly going clockwise we see; Adult fly, fly eggs, 1st_{instar, 2}nd_{instar, 3}rd

instar and the pupa. After hatching of the pupa the cycle repeats itself.

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and hair. An important factor in decomposition is the fact that blowfly larvae are responsible for ingesting 95% of the body mass. The eggs are laid on the body and when they hatch the larvae have direct access to a food source. More

information about the development of the larvae after hatching and the different life cycles can be found in the next chapter. When the drying phase (skeletal bone decomposition) of the body occurs other arthropods are attracted to the tissue of the body as well as the runoff of fluids from the body. When the species that colonized the body are identified, this knowledge can be used to determine a PMI [3][4][5][7].

4. Cuticular hydrocarbons

The Cuticular HydroCarbons (CHC) are one of the chemical compounds present in the lipid layer of insect cuticles. CHC are composed long linear chains of carbon and hydrogen atoms. These chains are mainly alkanes and alkenes and although there function is not entirely sure, it seems that there primarily function is to limit water loss (preventing dehydration).

Although the CHC can have multiple functions, for example ants use the CHC for communication and recognition, and it prevents the insect from external attacks from bacteria, fungi and insecticides. Also they can serve for pheromones and kairomones production.

- Pheromones are a substance secreted by the insect which influences

other individuals behaviour of the same species.

- Kairomones are semiochemicals emitted by the insect which create a reaction between the insect and nature, without benefitting the emitter but benefits a individual other species.

Hydrocarbons are found on almost all insect cuticles, however the where the hydrocarbons are stored and produces is not entirely sure. In flies the production of hydrocarbons is believed to be under direct control of ecdysteroid hormones that are indirectly influenced by the juvenile hormone (Wicker and Jallon 1995). Other studies show that the hydrocarbon production occurs in the sub-cuticular abdominal cells of adult flies. Hydrocarbons are transported to target tissues, for example to the ovaries cause the eggs of the insect require protection from water loss (dehydration), and pheromone or hydrocarbon-emitting glands. Although there can be several glands that produce the hydrocarbons, this can be function dependent for specific kinds of hydrocarbons.

The principle role of cuticular hydrocarbons is controlling the trans-cuticular water flux in insects due to their high surface volume ratio. The hydrocarbons on the cuticle account for only 0.1% of the total mass of the insect. Hydrocarbons are very non-polar compounds and together with the molecule structure, which makes it possible to nicely layer alkanes with each other, make a layer for the insects that prevent them from dehydration and wetting.

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When an in insect is covered by water the weight of the insect can increase massively compared to his own weight, the non polarity of hydrocarbons prevent this from happening. As mentioned above the hydrocarbons can also work as a signalling mechanism in some insect species. In the article of Howard and Blomquist (2005) six different areas of signalling (cuticular) hydrocarbons are indentified that may play a important role, these are: species and gender recognition, nest-mate recognition, task-specific cues, dominance, chemical mirmicry and acting as primer pheromones.

4.1 Hyrdrocarbons, flies and PMI

The cuticle of all insects are covered with a thin layer of epiticular layer of wax. This layer consist many different chemical structures such as hydrocarbons, alcohols, fatty acids, waxes, acylglycerides, phospholipids and glycolipids. The free lipids in the waxy layer consist a majority of hydrocarbons on almost all of the insects that are studied so far. The hydrocarbons are found in all life stages and are very stable on every insect, like on the blowfly mentioned in paragraph 3. Their biosynthesis is genetically based and modulated by factors such as

temperature, diet and reproductive stage. Necrophagous insects are very

important for estimating the PMI, to establish the PMI a method by identifying the hydrocarbons on different life stages of a blowfly can be used. The composition of hydrocarbons is not static but changes over time.

The differences in this hydrocarbon profile occur as part of the development of larvae into adult flies. Also the hydrocarbon profile can differ between different species of blowflies, this can be used as a identification marker on the unknown found species.

To get the potential of determining age of feeding and post feeding larvae, the changes of the Cuticular hydrocarbons (CHC) are analysed. To get the age of larvae the CHC-profile needs to be analysed daily. If there are changes over time in this CHC-profile it will be specific for a certain species, but more importantly specific for a particular moment in the life cycle of a larvae to adult fly.

Hydrocarbons found on the cuticle vary from C17 – C35. Not only CHC of the larval stage in the lifecycle of a blowfly are analysed, but also in eggs, eggshells, pupae, puparial cases and adult flies.

When the profile can be determined for the different life stages and what day or week the stage is in, the use of hydrocarbons can be a very useful tool for estimating the PMI of a body [3,6,7,9,14-22,24].

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5. Methodology

In the next few paragraphs the matrials and methods used in the project are described. Several steps are taken before the results can be concluded this is also explained in the results paragraph 6.

5.1 Insect materials

The insect material used for this project were obtained from Calliphora vicina colony reared and maintained in the lab and under inside conditions (231oC). They were fed with sugar, water and get eggs of the adults, pork chop was added to the cage. The larvae were fed mince meat which was placed on a petri dish on top of saw dust in a rearing box. The larvae were reared at 26oC in a incubator with high humidity. During the post feeding stage the larvae move away from the meat to the saw dust. The pupae were collected in plastic cups and sprayed every other day to keep the pupae damp. The pupae were daily checked for hatching. As soon a large amount (200 puparial cases) of flies hatched the puparial cases were taken a plastic tub. The bottem of the tub had holes in it so rain water could run through, also a layer of earth (from outside) was added to the tub to simulate outside conditions. The same day the tub was put outside with a data logger for temperature and humidity and weekly extractions were taken for hydrocarbons profile from the puparial cases.

5.2 Sample preparation

Liquid extraction with hexane was used to extract the hydrocarbons from the puparial cases. Two cases were pooled together to ensure the concentration was sufficient enough for the GC-MS to detect the hydrocarbons and for each day 10 repeats were extracted. As the puparial cases are exposed to outside conditions more, the concentration of the compounds were expected to degrease. The cases were placed into a GC vial with hexane ensuring that the case was submerged (300l of hexane). It was then left for 15 to 20 minutes and the hexane is removed and transferred to a GC-insert vial and left to dry down completely. The extracts were redissolved in 30 l of hexane and a 2 l aliquot was injected into the GC-MS with a autosampler [3,7,21].

5.3 Chemical Analysis: GC– MS

Chemical analysis of all extracts was carried out on an Agilent Technologies 6890N Network GC system with a split/splitless injector at 250oC, a Restek Rxi-1 capillary column (30m x 0.25 mmID, 0.25μm film thickness) and coupled to an Agilent 5973 Network Mass Selective Detector. The GC was coupled to a

computer and data processed with Agilent Chemstation software. Elution was carried out with helium at 1mL/min.

The oven temperature was programmed to be held at 50oC for 2 minutes then ramped to 200oC at 25oC/min, then from 200oC to 260oC at 3oC /min and finally

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from 260oC to 320oC at 20oC /min where it is held for 2 minutes. The mass spectrometer was operated in Electron Ionisation at 70 eV, scanning from 40 – 500 amu at 1.5 scans s-1. Hydrocarbons were identified using a library search (NIST08), the diagnostic fragmented ions and the retention index (Kovats index (paragraph 2.5)).

5.4 Statistical interpretation results

The calculations were carried out using multivariate add-ins to Microsoft Excel, which was created by Tom Thurston. All data were normalised to a mean of zero and a standard deviation of unity prior to the PCA calculation. Before PCA could be calculated, the peak areas were integrated using Agilent Chemstation

software and only the compounds that appeared on the auto-integration function in the software were used. Unless the peaks looked relevant and the mass

spectrum showed a hydrocarbon profile, the peaks were manually integrated afterwards. The PCA output is usually interpreted using a scatter-plot where the relative contributions of two particular components to each chromatogram are displayed. This shows the grouping of chemically similar samples and repeats, which have a correlation in particular variation of compounds. In this project ten repeats of every extraction interval is taken and it is very important that during the integration the variation between these repeats is minimized so the natural random variation between concentrations (peak areas) cannot be seen as major differences in the calculation [21,23].

5.4.1 Food competition experiment

Methods used in the food competition can be found in report of first 4,5 months internship at Keele University ‘Entomology & Analysis of hydrocarbons on

blowflies. In short the food competition experiment was setup to look at the larval length between different population of maggots in a rearing environment. The length is measured every 3 days until the larvae are pupae, on the 3 day intervals also extractions are taken to analyse the hydrocarbon profile.

Identification of the compounds are done the same way the puparial case project. In the first 4,5 months the internship was not focussed on the chemistry of the results but the results for this project is reanalysed for PCA and some new conclusions can be made from these results. Besides the further analyses was practice for the graduation project the interesting but discussible results of this experiment are described and shortly discussed in this report as well [25].

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6. Results

In this chapter the results are described. Starting from chromatograms to raw data on peak areas and compounds, multiple steps are taken to come to a more workable and explainable result. After these steps the conclusion and discussion can be drawn.

6.1 Overlay chromatograms

The chromatograms obtained after analyses on the GC were first overlaid with each other to look at major peak differences. The concentration of the hydrocarbons can change over time in puparial cases, but the whole HC-profile can change within the life stages of larvae.

Because the relevant peaks in the chromatograms are later indentified with the MS-spectrum, this first overlay can give a bit of information on what to expect in further analyses. Also the peak shape can be analysed

which is important information for the dilution of the samples before analyses on the GC-MS. A to high concentration in the sample will result in fronting peaks in the chromatogram (figure 7).

Figure 8: A overlay of chromatograms from 2 repeats of 2 extraction intervals. Where the differences of peak area (concentration) between the different intervals can be seen some examples are marked with the red arrows. The figure shows the chromatogram from retentiontime 21 to 25. The complete chromatograms goes from 0 to 32 minutes were minute 19 to 32 is used for compound analyses.

Figure 7: C27 Alkane, where the concentration in the sample oversaturated the detector, which results in fronting peaks. A long increasing line which can hide other smaller (lower concentration) compounds.

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In figure 8 an overlay of chromatograms on different time interval (week 1 & week 5) from puparial case extractions is shown. The red stripes in the figure show where the differences are already seen with an just an overlay between the samples. As expected there is a decrease in compounds seen in the

chromatogram the longer the samples were exposed to the outside conditions. The figure shows only a small fragment of the chromatogram, from retention time (Rt) 21 to 25 minutes. The peaks that were indentified and used in all the repeats of this project were from 19 – 32 minutes.

6.2 Identifying compounds

After the overlay the peaks are indentified according to the fragmentation pattern of the compound obtained from the MS, and the peak retention time with the peak area of the individual compounds are transferred to excel. This is done for each relevant compound. Relevant compounds are all hydrocarbons, identified acids or lipids are not included in the data file. Chapter 2 explains more about the characteristic patterns of different hydrocarbons after analyses with mass

spectrometry. With this theory and the retention index, all the compounds found in the samples were indentified. An example of the data file created in Excel with the areas and compounds is shown in the table on the next page.

Courtyard PC Data Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7

PC1 PC1 PC1 PC1 PC1 PC1 PC1 Retention

Compound Rt Area Area Area Area Area Area Area index

C24 Alkane 19.284 16001929 21943901 13977153 10912523 8465426 11856236 22094424 2400

6Me + 7Me C23 19.493 8435263 12720028 1000 1000 1000 1000 15251687 2430

C25 Alkane 21.387 7,87E+08 8,3E+08 3,98E+08 3,14E+08 2,73E+08 3,01E+08 8,36E+08 2500

3 ethyl C24 22.874 4,41E+08 4,05E+08 97140267 22874987 55002562 63575020 4,81E+08 2574

5,9 dimethyl C25 23.058 20433600 24593724 20196912 4723467 9136891 22671502 29249251 2583

C26 Alkane 23.394 1,78E+08 1,87E+08 1,6E+08 1,36E+08 1,06E+08 1,23E+08 2,17E+08 2600

unknown HC 23.603 1,21E+08 1,27E+08 59854376 27007326 54705084 47371227 1,58E+08 2609

Table 1 shows the first repeat out of 10 of every extraction interval. The area’s correspond to the concentration of the compound present in the sample, the Rt is the retention time when the compound elutes (leaves the column). The table shows a pattern in the first 2 weeks and show a bigger differences in areas from the compounds in week 3 to 6. Week 7 has more similarities to week 1 and 2, this is not expected but this result will be discussed in the conclusion/discussion paragraph. More compounds are identified in table 2 to give an overvieuw of the hydrocarbons present in the samples on the specific retention times. Uknown compounds have a mass spectrum that is unclear and it is unclear to specify the fragmentation profile.

Table 1: This table shows relevant compounds (hydrocarbons) with their Retention times (Rt) and peak areas. The peak area is in proportion to the concentration of the compound in the sample. And the table gives an example of compounds from 1 repeat of every extraction interval. Boxes are given a colour (red & green) to show a

correlation in area from a fraction of the compounds found.

Table 2: An overview of 24 compounds identified with help of their fragmention profile obtained from the MS and calculation of the retention index (RI). Identification is confirmed with the mass spec and not with just the Retention index value, because the fragmentation gives more information than the RI.

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Compound Rt Retention index Compound Rt Retention index C25 Alkane 21.387 2500 4MeC26 24.608 2658 10MeC25 22.042 2533 Unknown HC 24.740 2667 9MeC25 22.088 2536 C27 24.939 2702 7MeC25 22.191 2541 Unknown HC 25.731 2714 Dimethyl Br 22.368 2550 11MeC26, 13MeC26 25.772 2730 Unknown Br HC 22.625 2562 11MeC26, 13MeC26 25.987 2732 3MeC25 22.874 2574 9MeC26 26.284 2739 5,9DiMeC25 23.058 2853 5MeC26 26.331 2748 C26 23.394 2600 Unknown HC 26.454 2762 Unknown HC 23.603 2630 11,17DiMeC26 26.625 2777 13MeC26 24.091 2635 Unknown HC 26.895 2784 Unknown HC 24.200 2653 Unknown HC 27.187 2792

6.3 Principal Component Analysis

The results shown in the table above is just a fraction of compounds that are included in the PCA calculation in total 58 compounds were included in the data file. PCA (graph 1) is used to create a single data point for every repeat and all the compounds. This makes the analyses of the total results and the correlation between the repeats more workable.

Graph 1: Principal component analyses of all 58 hydrocarbons found on the specific intervals of puprial cases exposed to the outdoors. A spread of data points can be seen but also some intervals that are grouped. The ‘jump’, the point where the compounds has a bigger variation between each other is seen after week 2. Week 3, 4, 5 and 6 are very similar in compounds present and in their concentration.

PCA of all hydrocarbons found on/in C. vicina puparial cases

PC3 PC2 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1 -0.2 -0.15 -0.1 -0.05 0 0.05 0.1 0.15 0.2 0.25 0.3 Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7

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Looking at the PCA results a clear separation of intervals is shown in the graph. Week 1,2 and 7 are nicely grouped together as well as week 3, 4, 5 and 6. Week 7 is not expected to group together with the early weeks, but the results will be discussed in the next chapter. Looking at previous results the separation is caused by decreasing of hydrocarbon concentrations present in the puparial cases. One PCA point of week 6 (orange dot) seems very off from the rest of the analyses, because of the fact it’s only one of the ten repeats it is safe to say that something went wrong in either the analyses or in sample preparation.

The jump where the different intervals differ the most in the PCA might be

temperature dependent, that is suggested when the PCA (graph 2A) is compared to previous results analysed by PhD student Hannah Moore (graph 2B). The same method and equipment is used for her analyses. In Hannah Moore’s results the jump is already shown after day 1 and week 2, 3, 4 and 5 are grouped and then a jump after week 5. Because day 1 is not taken from the outside puparial cases this result will be ignored. Still there is a shift seen on a different interval. With this project the jump for major differences between the intervals takes longer.

Graph 2A & B: Graph A shows the same information as seen in graph 1, but a comparison is made with graph 2B; the previous results from PhD student Hannah Moore on C. Vicina puparial cases in 2010 where the puparial cases were kept in lab conditions (+/- 23 degrees). A similar pattern is found in the fact that a ‘jump’ occurs the longer the puparial cases are empty. This means the hydrocarbon profile did also change but in a different velocity then the outdoor samples shown in 2A.

PCA of Branced hydrocarbons only found on/in C. vicina puparial cases

PC3 v

PCA results Hannah Moore 2010 Branched only C. Vicina puprial cases PC3

A

B

-0.4 -0.2 0 0.2 0.4 0.6 0.8 -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 -0.2 -0.1 0 0.1 0.2 0.3 0.4 -0.15 -0.1 -0.05 0 0.05 0.1 Day 1 Wk 2 Wk 3 Wk 4 Wk 5 Wk 6 Wk 7 Wk 8 Mth 3 Mth 4 Mth 5 PC4 P C 3

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Day

3 Day

6 Day

9 6.3.1 Food competition Experiment PCA

As mentioned in the methods, paragraph 5.4.1, in this chapter the results are described from the food competition experiment which started in the first 4,5 months of the internship. Because of the interesting first results further analyses is carried out with PCA after indentifying the compounds found in the

chromatograms (with help of the MS).

In the first PCA shown in graph 3 all compounds including acids and possible lipids are taken in with their peak area and added to the PCA calculation. After trying out different combinations of plotting the different PC’s the result which shows the best separation is taken and discussed. Graph 4 shows the same results but only branched and non-branched hydrocarbons are taken in the PCA. A noticeable result which wasn’t not seen in the other project is that the 10 repeats are not all nicely grouped. Day 6 kept giving problems in the PCA results, possible reasons for this are discussed in paragraph 7.1.

Day 3

Day 9

Day 6

Graph 3: PCA results food competition experiment with PCA PC3 and PC4. All compounds including acids and lipids are included in the PCA calculation. The red circle shows unexpected results of some repeats in a extraction interval. The other coloured circles show the grouped 3 day extraction intervals.

PC4 PC3

PC2

PC5

Graph 4: PCA results food competition experiment with PCA PC2 and PC5. This PCA result are calculated with hydrocarbons only (branched and non-branched). The red circle shows unexpected results of some repeats in a extraction interval. The other coloured circles show the grouped 3 day extraction intervals.

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7. Conclusion & Discussion puparial case project

The expectations for this project was the degrease of hydrocarbons present in the empty puparial case coming from the adult fly leaving the pupae. As it can be read in paragraph 3, during the lifecycle of the larvae into the adult fly the hydrocarbon profile changes with the different life stages. Because the puparial cases are not growing or living organisms the hydrocarbon profile does not change in its compounds, but they do in concentration. This can also be seen in the results in the PCA (graph 1). Week 1, 2 and 7 are grouped together and after week 2 a jump accours where week 3, 4, 5 and 6 are grouped. This means that the concentrations of a combination of peaks (the hydrocarbon pattern) has a large variation compared to the early weeks. This is also seen in the table in paragraph 6.2, some hydrocarbons degrade faster than others. Because the PCA looks for overall patterns and similarities a minor random natural change in concentration won’t be seen as a jump compared to the other repeats. Looking at the calculated results from the first 6 weeks it can be concluded that a large decrease in concentration of compounds occur after week 2. The excel data file shows that some compounds even disappear, or have such a low concentration it can’t be detected with GC-MS. These results can be used to assist in a

determination of the time the puparial cases are exposed to the outside. And in a forensic context when found near a body, to age the puparial case. This

information could help in the suggestion of different generations of flies that may have infiltrated the body in earlier stages of decomposition.

When week 7 is included in the PCA it groups with week 1 and 2 what suggests this interval has the same concentration and hydrocarbon pattern as the puparial cases in the early weeks. Looking at the theory mentioned above it is impossible the pattern is similar because no new compounds or a increase in concentration can get into the puparial case unless it is from conditions from the outdoor environment, although this is very unlikely. During the integration and

identification of the peaks in the chromatograms, the repeats up to week 6 had quite a few compounds that oversaturated the detector in the GC what expresses in fronting peaks. The risk of these peaks is that compounds or in this case

hydrocarbons with small concentration won’t occur in the chromatogram because the small peak will disappear in the big area of this peak. The peaks in week 7 were sharper and not fronting, but with the identification more peaks showed up which were not seen because of oversaturated peaks in earlier extraction

intervals. This fact would suggest that the concentration found will be lower than the first few weeks, but the integration shows otherwise. The reason for this might be a more accurate detection of the compound and also a more accurate integration in the identification software, which resulted in a similar pattern with the first few weeks.

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Another aim of the project was to compare the outdoor conditions to the indoor analyses on the puparial cases which were analysed by PhD student Hannah Moore in 2010. As shown in the results paragraph a similar pattern of a shift in hydrocarbon profile is found when the puparial cases are aging. Because of the time spend of the internship the amount of extraction intervals could not be similar to the previous results of Hannah Moore, but looking at the PCA results up to week 8 there is also 1 jump in this amount of time, the only major difference is that the moment of this jump is after day 1 and week 5 compared to the outside results on week 2 (and week 6, thinking the week 7 results are accurate). This difference might be explained because of the exposure of temperature

differences, the puparial cases outside were under a lot of temperature changes and were in a more chilled environment. Indoor conditions were +/- 23 degrees Celcius and constant. Hydrocarbons in the puparial cases will vaporize faster under a constant and higher temperature of 23 degrees then the outdoor conditions. With the outdoor samples a data logger for the temperature was setup and the average temperature over the 7 weeks calculated at +/- 14 degrees Celcius. The data logger was set to measure the temperature every 30 minutes for 7 weeks straight, the samples were taken into the lab for 5 minutes on the extraction intervals (weekly) but this duration is expected not to have any effect on the hydrocarbon profile of the puparial cases.

7.1 Conclusion & Discussion food competition experiment

Looking at just the size, there are differences between the rearing boxes. So that suggests that the rearing environment influences the growth/length. With this finding and combining the MS-spectra plus PCA with these results, there are similarities in compounds on the extraction days. It is seen that the PCA groups certain days of the larvae together but in day 6 a noticeable difference with 5 repeats of the 10 taken on a day is present. This could be due errors made with indentifaction or that the larvae are in a different life stage then the others on the same day. Looking at the PCA results graph 4, with all compounds found in the samples, shows the best separation between the intervals. From this it can be suggested that not just hydrocarbons are responsible for changes during the life cycle. Still there are similarities found in the PCA which show that although the length between the larvae are different, the larvae are in the same stage of their life cycle. Final conclusion still stands that PCA gives reasonable results but more data is required to conclude the influences of (over)crowding in rearing boxes on the age and compounds present on the cuticle of the larvae.

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8. Future Work on puparial case project

For future work on this project there are multiple actions that can be taken to obtain more information on the differences (decrease) seen in the concentration of hydrocarbons in empty puparial cases. Although the main goal for this project was to compare the results with the inside conditions, some aspects of the sample preparation can be looked at. The concentration of the puparial cases from the outdoor environment was to high (noticed after GC-analyses). Because all the samples were ran in a big batch on the autosampler a high concentration of compounds was not seen in the preparation or before identification. Because the method was working well before with 2 puparial cases for the extractions it was assumed that the concentration wouldn’t cause fronting peaks in this

analysis. In future work the concentration needs to be checked and looking at the results now, the concentration must be significant enough to find the same amount of compounds with 1 puparial case in the method (extraction).

Also more extraction intervals should be taken to get a broader insight in the changes that occur the longer the puparial cases are exposed to outdoor or indoor environments and also to compare a longer period with previous results gather starting from 2010. As seen in the results in paragraph 6, the temperature seems to an have influence on the degradation of compounds present in the empty puparial cases, in future work a batch of puparial cases can be put on different constant temperatures in for example a incubator to analyse big

changes in hydrocarbon pattern differ according to temperature levels with PCA analyses. This can give more insight on the effects of outdoor effects as well. Another aspect which can give more insight in the change in hydrocarbon profile, is to indentify every hydrocarbon (including branched) and analyse the individual hydrocarbons in terms of percentage and decrease. When it is known which (branched) hydrocarbons are responsible for a major differ on a certain interval, a more accurate change and with that a ‘age’ of the puparial case can be

determined, or maybe even the effects of temperature levels/change.

8.1 Future work food competition experiment

Looking at the conclusion / discussion so far in this experiment, more research is needed to really conclude the effects on the amount of larvae in a (rearing) environment. More extraction days are needed to the determine the age of the larvae more accurately. The five odd results in day 6 can be due a GC error or indentifying error, but could be cause of a different life stage of the larvae as well. With the analyzed results it is hard to determine which of these suggestions is the right one. Also more accurate measurement of the larvae length can give more insight in the differences or similarities. This combining with more

extraction days and identifying all the compounds of the MS spectra, it could give a better insight of the relation between the different factors in the larvae.

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9. References

[1] Training Guide; Agilent Technologies: Fundamentals of GC-MS Agilent Technologies, Inc

Rev 1- November 2006

[2] Quantitative Chemical Analysis Daniel C. Harris

Freeman, Sixth Edition, 2003

[3] Current concepts in Forensic Entomology

Amendt, J.; Goff, M.L.; Campobasso, C.P.; Grassberger, M. (Eds.) 1st Edition., 2010

ISBN: 978-1-4020-9683-9 [4] Forensic entomology Dr. Dorothy Gennard

Wiley; 1 edition (April 20, 2007) ISBN: 978-0470014790

[5] Essential Forensic Biology A. Gunn

John Wiley and Sons Ltd, 1 edition, april 2006 ISBN: 978-0470012772

[6] Puparial case hydrocarbons of Chrysomya megacephala as PMI indicator Guang H. Zhu, Xiao H. Xu, Xiao J. Yu, Yuan Zhang, Jiang F. Wang

Forensic Science International 169 (2007) 1–5

[7] Development changes of cuticular hydrocarbons in Chrysomya rufifacies larvae: potential for determining larval age

G.H. Zhu, G.Y. Ye, C. Hu, X.H. Xu and K. Li

Medical and Veterinary Entomology (2006) 20, 438–444 [8] Journal of Chemical Ecology

Volume 14, Number 3, March 1988 ISSN 0098-0331

[9] Journal of Chemical Ecology

Volume 24, Number 11, November 1998 ISSN 0098-0331

[10] Kovats index, Retention index

http://www.standardbase.hu/tech/GCKovats.pdf Consulted on 19th_{April 2011}

[11] Encyclopedia of Forensic & Legal medicine vol. 3

Roger Byard, Tracey Corey, Carol Henderson, Jason Payne-James

Academic Press; 1 edition (July 20, 2005) ISBN: 978-0125479707

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[12] Encyclopedia of Forensic & Legal medicine vol. 2

Roger Byard, Tracey Corey, Carol Henderson, Jason Payne-James

Academic Press; 1 edition (July 20, 2005) ISBN: 978-0125479707

[13] Forensic Entomology

http://sciencespot.net/Media/FrnsScience/forenentocard.pdf Consulted on 20th_{april 2011}

[14] Forensic Entomology: Insects in Legal Investigations

http://www.forensicentomology.com/definition.htm

Consulted on 20th_{april 2011}

[15] Ontogenetic study of three Calliphoridae of forensic importance through cuticular hydrocarbon analysis

O. ROUX, C. GERS and L. LEGAL

Medical and Veterinary Entomology (2008) 22, 309–317 [16] Puparial case hydrocarbons of Chrysomya megacephala as an indicator of the postmortem interval

Guang H. Zhu, Xiao H. Xu, Xiao J. Yu, Yuan Zhang, Jiang F. Wang Forensic Science International 169 (2007) 1–5

[17] Flies as Forensic Indicators Bernard Greenberg

Department of biological Sciences, University of Illinois at Chicago, Chicago, Illinois 60680, J. Med, Entomol. 28(5): 565-577 (1991)

[18] Effect of temperature on Lucilia sericata (Diptera: Calliphordae) development with special reference to the isomegalen- and isomorphen-diagram

M. Grassberger, C. Reiter

Forensic Science International 120 (2001), 32-36

[19] Ontogenetic study of three Calliphoridae of forensic importance through cuticular hydrocarbon analysis O. Roux, C. Gers, L. Legal

Medical and Veterinary Entomology (2008) 22, 309–317 [20] Forensic Entomology in Germany

J. Amendt, R. Krettek, C. Niess, R. Zehner, H. Bratzke Forensic Science International 113 (2000), 309-314

[21] Potential use of hydrocarbons for ageing and identifying Lucilia sericata blowfly larvae to establish the Post-mortem Interval (PMI)

H. Moore, C. Adam, F.P. Drijfhout Paper draft

[22] Cuticular Hydrocarbons of Calliphora vomitoria (Diptera): Relation to Age and Sex

M. Trabalon, M. Campan, J. Clement, C. Lange, M. Mique General and comparative endocrinology 85 (1992), 208-216 [23] Statistics and Chemometrics for Analytical Chemistry J. N. Miller, J. C. Miller

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Fifth edition

ISBN: 0-131-29192-0

[24] The Insects: an outline of entomology P.J. Gullan, P.S. Cranson

Chapman & Hall, London; 1994 ISBN: 978-1-4051-1113-3

[25] Report of first 4,5 months internship at Keele University ‘Entomology & Analysis of hydrocarbons on blowflies’

Deena van Logchem 18 februari, 2011

Forensic science

Keele University Internship