A comparative analysis of stem cell differentiation on 2D and 3D substrates using Raman microspectroscopy.

Chondrogenesis is a complex cellular process that involves the transformation of mesenchymal stem cells (MSCs) into chondrocytes, the specialised cells that form cartilage. In recent years, three-dimensional (3D) culture systems have emerged as a promising approach to studying cell behaviour and development in a more physiologically relevant environment compared to traditional two-dimensional (2D) cell culture. The use of these systems provided insights into the molecular mechanisms that regulate chondrogenesis and has the potential to revolutionise the development of new therapies for cartilage repair and regeneration. This study demonstrates the successful application of Raman microspectroscopy (RMS) as a label-free, non-destructive, and sensitive method to monitor the chondrogenic differentiation of bone marrow-derived rat mesenchymal stem cells (rMSCs) in a collagen type I hydrogel, and explores the potential benefits of 3D hydrogels compared to conventional 2D cell culture environments. rMSCs were cultured on 3D substrates for 3 weeks and their differentiation was monitored by measuring the spectral signatures of their subcellular compartments. Additionally, the evolution of high-density micromass cultures was investigated to provide a comprehensive understanding of the process and complex interactions between cells and their surrounding extracellular matrix. For comparison, rMSCs were induced into chondrogenesis in identical medium conditions for 21 days in monolayer culture. Raman spectra showed that rMSCs cultured in a collagen type I hydrogel are able to undergo a distinct chondrogenic differentiation pathway at a significantly higher rate than the 2D culture cells. 3D cultures expressed stronger and more homogeneous chondrogenesis-associated peaks such as collagens, glycosaminoglycans (GAGs), and aggrecan while manifesting changes in proteins and lipidic content. These results suggest that 3D type I collagen hydrogel substrates are promising for in vitro chondrogenesis studies, and that RMS is a valuable tool for monitoring chondrogenesis in 3D environments.

Structural Features of Microvascular Networks Trigger Blood Flow Oscillations.

We analyse mathematical models in order to understand how microstructural features of vascular networks may affect blood flow dynamics, and to identify particular characteristics that promote the onset of self-sustained oscillations. By focusing on a simple three-node motif, we predict that network "redundancy", in the form of a redundant vessel connecting two main flow-branches, together with differences in haemodynamic resistance in the branches, can promote the emergence of oscillatory dynamics. We use existing mathematical descriptions for blood rheology and haematocrit splitting at vessel branch-points to construct our flow model; we combine numerical simulations and stability analysis to study the dynamics of the three-node network and its relation to the system's multiple steady-state solutions. While, for the case of equal inlet-pressure conditions, a "trivial" equilibrium solution with no flow in the redundant vessel always exists, we find that it is not stable when other, stable, steady-state attractors exist. In turn, these "nontrivial" steady-state solutions may undergo a Hopf bifurcation into an oscillatory state. We use the branch diameter ratio, together with the inlet haematocrit rate, to construct a two-parameter stability diagram that delineates regimes in which such oscillatory dynamics exist. We show that flow oscillations in this network geometry are only possible when the branch diameters are sufficiently different to allow for a sufficiently large flow in the redundant vessel, which acts as the driving force of the oscillations. These microstructural properties, which were found to promote oscillatory dynamics, could be used to explore sources of flow instability in biological microvascular networks.

A mathematical model of antibody-dependent cellular cytotoxicity (ADCC).

Immunotherapies exploit the immune system to target and kill cancer cells, while sparing healthy tissue. Antibody therapies, an important class of immunotherapies, involve the binding to specific antigens on the surface of the tumour cells of antibodies that activate natural killer (NK) cells to kill the tumour cells. Preclinical assessment of molecules that may cause antibody-dependent cellular cytotoxicity (ADCC) involves co-culturing cancer cells, NK cells and antibody in vitro for several hours and measuring subsequent levels of tumour cell lysis. Here we develop a mathematical model of such an in vitro ADCC assay, formulated as a system of time-dependent ordinary differential equations and in which NK cells kill cancer cells at a rate which depends on the amount of antibody bound to each cancer cell. Numerical simulations generated using experimentally-based parameter estimates reveal that the system evolves on two timescales: a fast timescale on which antibodies bind to receptors on the surface of the tumour cells, and NK cells form complexes with the cancer cells, and a longer time-scale on which the NK cells kill the cancer cells. We construct approximate model solutions on each timescale, and show that they are in good agreement with numerical simulations of the full system. Our results show how the processes involved in ADCC change as the initial concentration of antibody and NK-cancer cell ratio are varied. We use these results to explain what information about the tumour cell kill rate can be extracted from the cytotoxicity assays.

An assessment of professionalism on students' Facebook profiles.

INTRODUCTION: With the advent of social media, healthcare professionals not only need to be conscious of professionalism in their face-to-face interactions but also in the electronic environment. The aim of this study was to assess the level of online professionalism on Facebook profiles available for public viewing of students from a dental school. MATERIALS AND METHODS: A search was performed via a new Facebook account of all students in the University Dental School (dental hygiene, dental nursing, dental science and dental technology). Profiles were categorised as 'private' or 'public'. Demographic details and photographs/comments of unprofessional behaviour were recorded for each individual Facebook profile. Each profile was subsequently scored with regard to professionalism based on a previously published score. RESULTS: There are a total of 287 students in the dental school. Of these, 62% (n = 177) had a Facebook account. Three per cent (n = 6) had a public account (fully accessible) whilst 97% (n = 171) had a private account (limited access); 36% (n = 63) of students mentioned the dental school/hospital on their profile; 34% (n = 60) had questionable content on their profile whilst 3% (n = 6) had definite violations of professionalism on their profile; and 25% (n = 44) had unprofessional photographs on their profile. Of those with unprofessional content, 52% (n = 23) of these had a documented affiliation with the dental school also visible on their profile. CONCLUSION: There was a concerning level of unprofessional content visible on students' Facebook profiles. Students need to be fully aware of their professional responsibility in the setting of social media.

Diversity and dynamics of the DNA- and cDNA-derived compost fungal communities throughout the commercial cultivation process for Agaricus bisporus.

Commercial cultivation of the button mushroom Agaricus bisporus is performed through the inoculation of a semipasteurized composted material. Pasteurization of the compost material prior to inoculation results in a substrate with a fungal community that becomes dominated by A. bisporus. However, little is known about the composition and activity in the wider fungal community beyond the presence of A. bisporus in compost throughout the mushroom cropping process. In this study, the fungal cropping compost community was characterized by sequencing nuc rDNA ITS1-5.8S-ITS2 amplified from extractable DNA and RNA. The fungal community generated from DNA extracts identified a diverse community containing 211 unique species, although only 51 were identified from cDNA. Agaricus bisporus was found to dominate in the DNA-derived fungal community for the duration of the cropping process. However, analysis of cDNA extracts found A. bisporus to dominate only up to the first crop flush, after which activity decreased sharply and a much broader fungal community became active. This study has highlighted the diverse fungal community that is present in mushroom compost during cropping.

Mathematical modelling of stretch-induced membrane traffic in bladder umbrella cells.

The bladder is a complex organ that is highly adaptive to its mechanical environment. The umbrella cells in the bladder uroepithelium are of particular interest: these cells actively change their surface area through exo- and endocytosis of cytoplasmic vesicles, and likely form a critical component in the mechanosensing process that communicates the sense of 'fullness' to the nervous system. In this paper we develop a first mechanical model for vesicle trafficking in umbrella cells in response to membrane tension during bladder filling. Recent experiments conducted on a disc of uroepithelial tissue motivate our model development. These experiments subject bladder tissue to fixed pressure differences and exhibit counterintuitive area changes. Through analysis of the mathematical model and comparison with experimental data in this setup, we gain an intuitive understanding of the biophysical processes involved and calibrate the vesicle trafficking rate parameters in our model. We then adapt the model to simulate in vivo bladder filling and investigate the potential effect of abnormalities in the vesicle trafficking machinery on bladder pathologies.

Vascular phenotype identification and anti-angiogenic treatment recommendation: A pseudo-multiscale mathematical model of angiogenesis.

The development of anti-angiogenic drugs for cancer therapy has yielded some promising candidates, but novel approaches for interventions to angiogenesis have led to disappointing results. In addition, there is a shortage of biomarkers that are predictive of response to anti-angiogenic treatments. Consequently, the complex biochemical and physiological basis for tumour angiogenesis remains incompletely understood. We have adopted a mathematical approach to address these issues, formulating a spatially averaged multiscale model that couples the dynamics of VEGF, Ang1, Ang2 and PDGF, with those of mature and immature endothelial cells and pericyte cells. The model reproduces qualitative experimental results regarding pericyte coverage of vessels after treatment by anti-Ang2, anti-VEGF and combination anti-VEGF/anti-Ang2 antibodies. We used the steady state behaviours of the model to characterise angiogenic and non-angiogenic vascular phenotypes, and used mechanistic perturbations representing hypothetical anti-angiogenic treatments to generate testable hypotheses regarding transitions to non-angiogenic phenotypes that depend on the pre-treatment vascular phenotype. Additionally, we predicted a synergistic effect between anti-VEGF and anti-Ang2 treatments when applied to an immature pre-treatment vascular phenotype, but not when applied to a normalised angiogenic pre-treatment phenotype. Based on these findings, we conclude that changes in vascular phenotype are predicted to be useful as an experimental biomarker of response to treatment. Further, our analysis illustrates the potential value of non-spatial mathematical models for generating tractable predictions regarding the action of anti-angiogenic therapies.

A multi-scale model of the interplay between cell signalling and hormone transport in specifying the root meristem of Arabidopsis thaliana.

The growth of the root of Arabidopsis thaliana is sustained by the meristem, a region of cell proliferation and differentiation which is located in the root apex and generates cells which move shootwards, expanding rapidly to cause root growth. The balance between cell division and differentiation is maintained via a signalling network, primarily coordinated by the hormones auxin, cytokinin and gibberellin. Since these hormones interact at different levels of spatial organisation, we develop a multi-scale computational model which enables us to study the interplay between these signalling networks and cell-cell communication during the specification of the root meristem. We investigate the responses of our model to hormonal perturbations, validating the results of our simulations against experimental data. Our simulations suggest that one or more additional components are needed to explain the observed expression patterns of a regulator of cytokinin signalling, ARR1, in roots not producing gibberellin. By searching for novel network components, we identify two mutant lines that affect significantly both root length and meristem size, one of which also differentially expresses a central component of the interaction network (SHY2). More generally, our study demonstrates how a multi-scale investigation can provide valuable insight into the spatio-temporal dynamics of signalling networks in biological tissues.

Raman spectroscopy for cytopathology of exfoliated cervical cells.

Cervical cancer is the fourth most common cancer affecting women worldwide but mortality can be decreased by early detection of pre-malignant lesions. The Pap smear test is the most commonly used method in cervical cancer screening programmes. Although specificity is high for this test, it is widely acknowledged that sensitivity can be poor mainly due to the subjective nature of the test. There is a need for new objective tests for the early detection of pre-malignant cervical lesions. Over the past two decades, Raman spectroscopy has emerged as a promising new technology for cancer screening and diagnosis. The aim of this study was to evaluate the potential of Raman spectroscopy for cervical cancer screening using both Cervical Intraepithelial Neoplasia (CIN) and Squamous Intraepithelial Lesion (SIL) classification terminology. ThinPrep® Pap samples were recruited from a cervical screening population. Raman spectra were recorded from single cell nuclei and subjected to multivariate statistical analysis. Normal and abnormal ThinPrep® samples were discriminated based on the biochemical fingerprint of the cells using Principal Component Analysis (PCA). Principal Component Analysis - Linear Discriminant Analysis (PCA-LDA) was employed to build classification models based on either CIN or SIL terminology. This study has shown that Raman spectroscopy can be successfully applied to the study of routine cervical cytology samples from a cervical screening programme and that the use of CIN terminology resulted in improved sensitivity for high grade cases.

An investigation of the influence of extracellular matrix anisotropy and cell-matrix interactions on tissue architecture.

Mechanical interactions between cells and the fibrous extracellular matrix (ECM) in which they reside play a key role in tissue development. Mechanical cues from the environment (such as stress, strain and fibre orientation) regulate a range of cell behaviours, including proliferation, differentiation and motility. In turn, the ECM structure is affected by cells exerting forces on the matrix which result in deformation and fibre realignment. In this paper we develop a mathematical model to investigate this mechanical feedback between cells and the ECM. We consider a three-phase mixture of collagen, culture medium and cells, and formulate a system of partial differential equations which represents conservation of mass and momentum for each phase. This modelling framework takes into account the anisotropic mechanical properties of the collagen gel arising from its fibrous microstructure. We also propose a cell-collagen interaction force which depends upon fibre orientation and collagen density. We use a combination of numerical and analytical techniques to study the influence of cell-ECM interactions on pattern formation in tissues. Our results illustrate the wide range of structures which may be formed, and how those that emerge depend upon the importance of cell-ECM interactions.

A spatially-averaged mathematical model of kidney branching morphogenesis.

Kidney development is initiated by the outgrowth of an epithelial ureteric bud into a population of mesenchymal cells. Reciprocal morphogenetic responses between these two populations generate a highly branched epithelial ureteric tree with the mesenchyme differentiating into nephrons, the functional units of the kidney. While we understand some of the mechanisms involved, current knowledge fails to explain the variability of organ sizes and nephron endowment in mice and humans. Here we present a spatially-averaged mathematical model of kidney morphogenesis in which the growth of the two key populations is described by a system of time-dependant ordinary differential equations. We assume that branching is symmetric and is invoked when the number of epithelial cells per tip reaches a threshold value. This process continues until the number of mesenchymal cells falls below a critical value that triggers cessation of branching. The mathematical model and its predictions are validated against experimentally quantified C57Bl6 mouse embryonic kidneys. Numerical simulations are performed to determine how the final number of branches changes as key system parameters are varied (such as the growth rate of tip cells, mesenchyme cells, or component cell population exit rate). Our results predict that the developing kidney responds differently to loss of cap and tip cells. They also indicate that the final number of kidney branches is less sensitive to changes in the growth rate of the ureteric tip cells than to changes in the growth rate of the mesenchymal cells. By inference, increasing the growth rate of mesenchymal cells should maximise branch number. Our model also provides a framework for predicting the branching outcome when ureteric tip or mesenchyme cells change behaviour in response to different genetic or environmental developmental stresses.

Raman micro spectroscopy for in vitro drug screening: subcellular localisation and interactions of doxorubicin.

Vibrational spectroscopy, including Raman micro spectroscopy, has been widely used over the last few years to explore potential biomedical applications. Indeed, Raman micro spectroscopy has been demonstrated to be a powerful non-invasive tool in cancer diagnosis and monitoring. In confocal microscopic mode, the technique is also a molecularly specific analytical tool with optical resolution which has potential applications in subcellular analysis of biochemical processes, and therefore as an in vitro screening tool of the efficacy and mode of action of, for example, chemotherapeutic agents. In order to demonstrate and explore the potential in this field, established, model chemotherapeutic agents can be valuable. In this study paper, Raman micro spectroscopy coupled with confocal microscopy were used for the localization and tracking of the commercially available drug, doxorubicin (DOX), in the intracellular environment of the lung cancer cell line, A549. Cytotoxicity assays were employed to establish clinically relevant drug doses for 24 h exposure, and Confocal Laser Scanning Fluorescence Microscopy was conducted in parallel with Raman micro spectroscopy profiling to confirm the drug internalisation and localisation. Multivariate statistical analysis, consisting of PCA (principal components analysis) was used to highlight doxorubicin interaction with cancer cells and spectral variations due to its effects before and after DOX spectral features subtraction from nuclear and nucleolar spectra, were compared to non-exposed control spectra. Results show that Raman micro spectroscopy is not only able to detect doxorubicin inside cells and profile its specific subcellular localisation, but, it is also capable of elucidating the local biomolecular changes elicited by the drug, differentiating the responses in different sub cellular regions. Further analysis clearly demonstrates the early apoptotic effect in the nuclear regions and the initial responses of cells to this death process, demonstrating the potential of the technique to monitor the mechanisms of action and response on a molecular level, with subcellular resolution.

Cellular discrimination using in vitro Raman micro spectroscopy: the role of the nucleolus.

Raman micro spectroscopy has attracted considerable attention over the last few years to explore its possible clinical applications as a non-invasive powerful label-free in vitro screening tool in cancer diagnosis and monitoring, subcellular analysis of biochemical processes, drug uptake, mode of action and mechanisms of interaction as well as toxicity of, for example, chemotherapeutic agents. However, in order to evaluate accurately the potential of Raman micro spectroscopy for such applications it is essential to optimise measurement and data processing protocols associated with subcellular analysis. To this end, in vitro differentiation of cell lines is a basic proof of concept for the potential of the technique, and although many studies have indicated successful differentiation based on Raman micro spectroscopy, it is important, as the measurement and processing techniques are improved, to establish the biochemical and subcellular basis of that discrimination. In this study, Raman micro spectroscopy is used to compare and differentiate normal and cancer cells from human lung origin, A549 adenocarcinoma cell line, Calu-1 epidermoid non-small-cell and BEAS-2B normal immortalized bronchial epithelium cell line. Spectra were taken from the three subcellular compartments, cytoplasm, nucleus and nucleolus and Principal Components Analysis was used to compare the spectral profiles between the cell lines and, coupled to Linear Discriminant Analysis, to explore the optimum sensitivity and specificity of discrimination. To support the analysis, Raman micro spectroscopy was coupled with Flow Cytometry, Confocal Laser Scanning Microscopy and Atomic Force Microscopy. While all subcellular regions can be employed to differentiate the normal and cancer cell lines, optimum discrimination sensitivity and specificity is achieved using the spectra from the nucleolar region alone. Notably, only the nucleolar spectral profiles differentiate the two cancer cell lines. The results point to the importance of the nucleolar regions in diagnostic applications of Raman microscopy as well as further applications in subcellular analysis of cytological processes.

Post-transcriptional regulation in the nucleus and cytoplasm: study of mean time to threshold (MTT) and narrow escape problem.

Messenger RNAs (mRNAs) can be repressed and degraded by small non-coding RNA molecules. In this paper, we formulate a coarsegrained Markov-chain description of the post-transcriptional regulation of mRNAs by either small interfering RNAs (siRNAs) or microRNAs (miRNAs). We calculate the probability of an mRNA escaping from its domain before it is repressed by siRNAs/miRNAs via calculation of the mean time to threshold: when the number of bound siRNAs/miRNAs exceeds a certain threshold value, the mRNA is irreversibly repressed. In some cases, the analysis can be reduced to counting certain paths in a reduced Markov model. We obtain explicit expressions when the small RNA bind irreversibly to the mRNA and we also discuss the reversible binding case. We apply our models to the study of RNA interference in the nucleus, examining the probability of mRNAs escaping via small nuclear pores before being degraded by siRNAs. Using the same modelling framework, we further investigate the effect of small, decoy RNAs (decoys) on the process of post-transcriptional regulation, by studying regulation of the tumor suppressor gene, PTEN: decoys are able to block binding sites on PTEN mRNAs, thereby reducing the number of sites available to siRNAs/miRNAs and helping to protect it from repression. We calculate the probability of a cytoplasmic PTEN mRNA translocating to the endoplasmic reticulum before being repressed by miRNAs. We support our results with stochastic simulations.

Mesoscopic and continuum modelling of angiogenesis.

Angiogenesis is the formation of new blood vessels from pre-existing ones in response to chemical signals secreted by, for example, a wound or a tumour. In this paper, we propose a mesoscopic lattice-based model of angiogenesis, in which processes that include proliferation and cell movement are considered as stochastic events. By studying the dependence of the model on the lattice spacing and the number of cells involved, we are able to derive the deterministic continuum limit of our equations and compare it to similar existing models of angiogenesis. We further identify conditions under which the use of continuum models is justified, and others for which stochastic or discrete effects dominate. We also compare different stochastic models for the movement of endothelial tip cells which have the same macroscopic, deterministic behaviour, but lead to markedly different behaviour in terms of production of new vessel cells.

An ordinary differential equation model for full thickness wounds and the effects of diabetes.

Wound healing is a complex process in which a sequence of interrelated phases contributes to a reduction in wound size. For diabetic patients, many of these processes are compromised, so that wound healing slows down. In this paper we present a simple ordinary differential equation model for wound healing in which attention focusses on the dominant processes that contribute to closure of a full thickness wound. Asymptotic analysis of the resulting model reveals that normal healing occurs in stages: the initial and rapid elastic recoil of the wound is followed by a longer proliferative phase during which growth in the dermis dominates healing. At longer times, fibroblasts exert contractile forces on the dermal tissue, the resulting tension stimulating further dermal tissue growth and enhancing wound closure. By fitting the model to experimental data we find that the major difference between normal and diabetic healing is a marked reduction in the rate of dermal tissue growth for diabetic patients. The model is used to estimate the breakdown of dermal healing into two processes: tissue growth and contraction, the proportions of which provide information about the quality of the healed wound. We show further that increasing dermal tissue growth in the diabetic wound produces closure times similar to those associated with normal healing and we discuss the clinical implications of this hypothesised treatment.

The resolution of inflammation: a mathematical model of neutrophil and macrophage interactions.

There is growing interest in inflammation due to its involvement in many diverse medical conditions, including Alzheimer's disease, cancer, arthritis and asthma. The traditional view that resolution of inflammation is a passive process is now being superceded by an alternative hypothesis whereby its resolution is an active, anti-inflammatory process that can be manipulated therapeutically. This shift in mindset has stimulated a resurgence of interest in the biological mechanisms by which inflammation resolves. The anti-inflammatory processes central to the resolution of inflammation revolve around macrophages and are closely related to pro-inflammatory processes mediated by neutrophils and their ability to damage healthy tissue. We develop a spatially averaged model of inflammation centring on its resolution, accounting for populations of neutrophils and macrophages and incorporating both pro- and anti-inflammatory processes. Our ordinary differential equation model exhibits two outcomes that we relate to healthy and unhealthy states. We use bifurcation analysis to investigate how variation in the system parameters affects its outcome. We find that therapeutic manipulation of the rate of macrophage phagocytosis can aid in resolving inflammation but success is critically dependent on the rate of neutrophil apoptosis. Indeed our model predicts that an effective treatment protocol would take a dual approach, targeting macrophage phagocytosis alongside neutrophil apoptosis.

Multiphase modelling of vascular tumour growth in two spatial dimensions.

In this paper we present a continuum mathematical model of vascular tumour growth which is based on a multiphase framework in which the tissue is decomposed into four distinct phases and the principles of conservation of mass and momentum are applied to the normal/healthy cells, tumour cells, blood vessels and extracellular material. The inclusion of a diffusible nutrient, supplied by the blood vessels, allows the vasculature to have a nonlocal influence on the other phases. Two-dimensional computational simulations are carried out on unstructured, triangular meshes to allow a natural treatment of irregular geometries, and the tumour boundary is captured as a diffuse interface on this mesh, thereby obviating the need to explicitly track the (potentially highly irregular and ill-defined) tumour boundary. A hybrid finite volume/finite element algorithm is used to discretise the continuum model: the application of a conservative, upwind, finite volume scheme to the hyperbolic mass balance equations and a finite element scheme with a stable element pair to the generalised Stokes equations derived from momentum balance, leads to a robust algorithm which does not use any form of artificial stabilisation. The use of a matrix-free Newton iteration with a finite element scheme for the nutrient reaction-diffusion equations allows full nonlinearity in the source terms of the mathematical model. Numerical simulations reveal that this four-phase model reproduces the characteristic pattern of tumour growth in which a necrotic core forms behind an expanding rim of well-vascularised proliferating tumour cells. The simulations consistently predict linear tumour growth rates. The dependence of both the speed with which the tumour grows and the irregularity of the invading tumour front on the model parameters is investigated.

Raman spectroscopic mapping for the analysis of solar radiation induced skin damage.

The effects of simulated solar irradiation of an artificial skin model have been examined using Raman spectroscopy and the results are compared with cytotoxicological and histological profiling. Samples exposed for times varying between 30 minutes and 240 minutes were incubated post exposure for a period of 96 hours. The cytotoxicological response as measured by the MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide] assay demonstrated a ~50% loss of viability of the artificial tissue after 120 minutes exposure. Histological staining of tissue sections showed considerable loss of cellular content in the epidermal layer at this endpoint. Raman spectroscopic mapping of tissue sections, coupled with K-means cluster analysis (KMCA) clearly identified the dermal and stratum corneum layers and differentiated further substructures of the epidermis. Post irradiation, a significant loss of DNA features in the basal layer was apparent in the results of the KMCA. Principal Components Analysis (PCA) of layers identified by the KMCA post exposure compared with controls indicated a significant increase in the lipidic signatures of the stratum corneum. In the dermal layer, little photodamage was observed, but a similar increase in lipidic signatures in the basal layer was accompanied by a decrease in DNA and protein contributions. The spectral profiles of the photodamage to the basal layer as identified by PCA are consistent over the exposure periods of 30-240 minutes, but an examination of the evolution of features associated with specific biochemical components indicated DNA damage and loss of lipidic signatures at the early exposure times, whereas changes in protein signatures appeared to evolve over longer periods. In comparison to the cytotoxicological responses, the study demonstrates that Raman spectroscopy can identify biochemical changes as a result of solar exposure at time points significantly earlier than changes in tissue viability are observed.