Working directly with probabilities in quantum field theory

We present a novel approach to computing transition probabilities in quantum field theory, which allows them to be written directly in terms of expectation values of nested commutators and anti-commutators of field operators, rather than squared matrix elements. We show that this leads to a diagrammatic expansion in which the retarded propagator plays a dominant role. As a result, one is able to see clearly how faster-than-light signalling is prevented between sources and detectors. Finally, we comment on potential implications of this approach for dealing with infra-red divergences

An updated report on the incidence and epidemiological trends of keratinocyte cancers in the United Kingdom 2013-2018

Introduction: The most common cancers in the UK are keratinocyte cancers (KCs): the combined term for basal cell carcinomas (BCCs) and cutaneous squamous cell carcinomas (cSCCs). Registration of KC is challenging due to high numbers and multiplicity of tumours per person. Methods: We provide an updated report on the descriptive epidemiology of trends in KC incidence for the resident populations of UK countries (England, Northern Ireland, Scotland and Wales) using population-based cancer registry and pathology report data, 2013-18. Results: Substantial increases in cSCC incidence in England, Scotland and Northern Ireland can be detected for the period of 2013-18, and the incidence of cSCC also increased in Wales from 2016 to 2018. In contrast, however, the pattern of annual change in the incidence of BCC across the nations differs. In England, the incidence of BCC declined slightly from 2016 to 2018, however, the overall trend across 2013-18 is not statistically significant. In Scotland, the incidence of BCC shows some variability, declining in 2017 before increasing in 2018, and the overall trend across 2013-18 was also not statistically significant. In Northern Ireland, the incidence of BCC increased significantly over the study period, and in Wales, the incidence of BCC increased from 2016 to 2018. One in five people will develop non-melanoma skin cancers (NMSC) in their lifetime in England. This estimate is much higher than the lifetime risk of melanoma (1 in 36 males and 1 in 47 females born after 1960 in the UK), which further highlights the burden of the disease and importance of early prevention strategies. Conclusions: We highlight how common these tumours are by publishing the first ever lifetime incidence of NMSC. Additionally, the first time reporting of the age standardised incidence of KC in Wales further confirms the scale of the disease burden posed by these cancers in the UK. With approximately one in five people developing NMSC in their lifetime, optimisation of skin cancer prevention, management and research are essential

Quantification of lentiviral vector copy numbers in individual hematopoietic colony-forming cells shows vector dose-dependent effects on the frequency and level of transduction

Lentiviral vectors are effective tools for gene transfer and integrate variable numbers of proviral DNA copies in variable proportions of cells. The levels of transduction of a cellular population may therefore depend upon experimental parameters affecting the frequency and/or the distribution of vector integration events in this population. Such analysis would require measuring vector copy numbers (VCN) in individual cells. To evaluate the transduction of hematopoietic progenitor cells at the single-cell level, we measured VCN in individual colony-forming cell (CFC) units, using an adapted quantitative PCR (Q-PCR) method. The feasibility, reproducibility and sensitivity of this approach were tested with characterized cell lines carrying known numbers of vector integration. The method was validated by correlating data in CFC with gene expression or with calculated values, and was found to slightly underestimate VCN. In spite of this, such Q-PCR on CFC was useful to compare transduction levels with different infection protocols and different vectors. Increasing the vector concentration and re-iterating the infection were two different strategies that improved transduction by increasing the frequency of transduced progenitor cells. Repeated infection also augmented the number of integrated copies and the magnitude of this effect seemed to depend on the vector preparation. Thus, the distribution of VCN in hematopoietic colonies may depend upon experimental conditions including features of vectors. This should be carefully evaluated in the context of ex vivo hematopoietic gene therapy studies

Housing Conditions Differentially Affect Physiological and Behavioural Stress Responses of Zebrafish, as well as the Response to Anxiolytics

Zebrafish are a widely utilised animal model in developmental genetics, and owing to recent advances in our understanding of zebrafish behaviour, their utility as a comparative model in behavioural neuroscience is beginning to be realised. One widely reported behavioural measure is the novel tank-diving assay, which has been often cited as a test of anxiety and stress reactivity. Despite its wide utilisation, and various validations against anxiolytic drugs, reporting of pre-test housing has been sparse in the literature. As zebrafish are a shoaling species, we predicted that housing environment would affect their stress reactivity and, as such, their response in the tank-diving procedure. In our first experiment, we tested various aspects of housing (large groups, large groups with no contact, paired, visual contact only, olfactory contact only) and found that the tank diving response was mediated by visual contact with conspecifics. We also tested the basal cortisol levels of group and individually housed fish, and found that individually housed individuals have lower basal cortisol levels. In our second experiment we found ethanol appeared to have an anxiolytic effect with individually housed fish but not those that were group housed. In our final experiment, we examined the effects of changing the fishes' water prior to tank diving as an additional acclimation procedure. We found that this had no effect on individually housed fish, but appeared to affect the typical tank diving responses of the group housed individuals. In conclusion, we demonstrate that housing represents an important factor in obtaining reliable data from this methodology, and should be considered by researchers interested in comparative models of anxiety in zebrafish in order to refine their approach and to increase the power in their experiments

A summary of the updated report on the incidence and epidemiological trends of keratinocyte cancers in the UK 2013–2018

Skin cancer is the commonest cancer in the UK. Skin cancer referrals via the two-week wait (urgent suspected cancer) pathway outnumber any other suspected malignancy.1, 2 The commonest skin cancers are keratinocyte cancers (KCs) which represents Basal Cell Carcinomas (BCC) and Cutaneous Squamous Cell Carcinomas (cSCC). Accurate KC incidence reporting is crucial for healthcare planning

Universal surface-enhanced Raman tags : individual nanorods for measurements from the visible to the infrared (514 – 1064 nm)

Surface-enhanced Raman scattering (SERS) is a promising imaging modality for use in a variety of multiplexed tracking and sensing applications in biological environments. However, the uniform production of SERS nanoparticle tags with high yield and brightness still remains a significant challenge. Here, we describe an approach based on the controlled co-adsorption of multiple dye species onto gold nanorods to create tags that can be detected across a much wider range of excitation wavelengths (514 – 1064 nm) compared to conventional approaches that typically focus on a single wavelength. This was achieved without the added complexity of nanoparticle aggregation or growing surrounding metallic shells to further enhance the surface-enhanced resonance Raman scattering (SERRS) signal. Correlated Raman and scanning electron microscopy mapping measurements of individual tags were used to clearly demonstrate that strong and reproducible SERRS signals at high particle yields (>92 %) were readily achievable. The polyelectrolyte-wrapped nanorod-dye conjugates were also found to be highly stable as well as non-cytotoxic. To demonstrate the use of these universal tags for the multimodal optical imaging of biological specimens, confocal Raman and fluorescence maps of stained immune cells following nanoparticle uptake were acquired at several excitation wavelengths and compared with dark-field images. The ability to colocalize and track individual optically encoded nanoparticles across a wide range of wavelengths simultaneously will enable the use of SERS alongside other imaging techniques for the real-time monitoring of cell-nanoparticle interactions

Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics

Timm W, Scherbart A, Boecker S, Kohlbacher O, Nattkemper TW. Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics. BMC Bioinformatics. 2008;9(1):443.Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides and proteins, however, is the fact that absolute quantification is severely hampered by the unclear relationship between the observed peak intensity and the peptide concentration in the sample. While there are numerous approaches to circumvent this problem experimentally (e. g. labeling techniques), reliable prediction of the peak intensities from peptide sequences could provide a peptide-specific correction factor. Thus, it would be a valuable tool towards label-free absolute quantification. Results: In this work we present machine learning techniques for peak intensity prediction for MALDI mass spectra. Features encoding the peptides' physico-chemical properties as well as string-based features were extracted. A feature subset was obtained from multiple forward feature selections on the extracted features. Based on these features, two advanced machine learning methods (support vector regression and local linear maps) are shown to yield good results for this problem (Pearson correlation of 0.68 in a ten-fold cross validation). Conclusion: The techniques presented here are a useful first step going beyond the binary prediction of proteotypic peptides towards a more quantitative prediction of peak intensities. These predictions in turn will turn out to be beneficial for mass spectrometry-based quantitative proteomics