The Classical Solution for the Bosonic String in the Presence of Three D-branes Rotated by Arbitrary SO(4) Elements

We consider the classical instantonic contribution to the open string configuration associated with three D-branes with relative rotation matrices in SO(4) which corresponds to the computation of the classical part of the correlator of three non Abelian twist fields. We write the classical solution as a sum of a product of two hypergeometric functions. Differently from all the previous cases with three D-branes, the solution is not holomorphic and suggests that the classical bosonic string knows when the configuration may be supersymmetric. We show how this configuration reduces to the standard Abelian twist field computation. From the phenomenological point of view, the Yukawa couplings between chiral matter at the intersection in this configuration are more suppressed with respect to the factorized case in the literature.Comment: 41 pages, 8 figure

Iron serum status, serum VEGF and oxidative stress pattern evaluation in canine cancer patients, focusing on mast cell tumours

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On the Origin of Divergences in Time-Dependent Orbifolds

We consider time-dependent orbifolds in String Theory and we show that divergences are not associated with a gravitational backreaction since they appear in the open string sector too. They are related to the non existence of the underlying effective field theory as in several cases fourth and higher order contact terms do not exist. Since contact terms may arise from the exchange of string massive states, we investigate and show that some three points amplitudes with one massive state in the open string sector are divergent on the time-dependent orbifolds. To check that divergences are associated with the existence of a discrete zero eigenvalue of the Laplacian of the subspace with vanishing volume, we construct the Generalized Null Boost Orbifold where this phenomenon can be turned on and off.Comment: 43 page

HyperPCA: a Powerful Tool to Extract Elemental Maps from Noisy Data Obtained in LIBS Mapping of Materials

Laser-induced breakdown spectroscopy is a preferred technique for fast and direct multi-elemental mapping of samples under ambient pressure, without any limitation on the targeted element. However, LIBS mapping data have two peculiarities: an intrinsically low signal-to-noise ratio due to single-shot measurements, and a high dimensionality due to the high number of spectra acquired for imaging. This is all the truer as lateral resolution gets higher: in this case, the ablation spot diameter is reduced, as well as the ablated mass and the emission signal, while the number of spectra for a given surface increases. Therefore, efficient extraction of physico-chemical information from a noisy and large dataset is a major issue. Multivariate approaches were introduced by several authors as a means to cope with such data, particularly Principal Component Analysis. Yet, PCA is known to present theoretical constraints for the consistent reconstruction of the dataset, and has therefore limitations to efficient interpretation of LIBS mapping data. In this paper, we introduce HyperPCA, a new analysis tool for hyperspectral images based on a sparse representation of the data using Discrete Wavelet Transform and kernel-based sparse PCA to reduce the impact of noise on the data and to consistently reconstruct the spectroscopic signal, with a particular emphasis on LIBS data. The method is first illustrated using simulated LIBS mapping datasets to emphasize its performances with highly noisy and/or highly interfered spectra. Comparisons to standard PCA and to traditional univariate data analyses are provided. Finally, it is used to process real data in two cases that clearly illustrate the potential of the proposed algorithm. We show that the method presents advantages both in quantity and quality of the information recovered, thus improving the physico-chemical characterisation of analysed surfaces.Comment: 20 pages, 8 pages of supplementary materia

Primary Corneal Squamous Cell Carcinoma in a Dog: Clinical and Histopathological Evaluation

An 8-year-old male pug with a 12-month history of a progressive nonpainful mass on the left cornea was evaluated. Ocular examination showed a severe bilateral keratoconjunctivitis sicca, pigmentary keratitis, and an exophytic irregular pink mass occupying approximately 75% of the total corneal surface of the left eye. A squamous cell carcinoma (SCC) was suspected on cytology, and clinical investigations showed no evidence of metastases. A transpalpebral enucleation was therefore performed, and the diagnosis of SCC was confirmed on histopathology. Immunohistochemical investigations showed that the neoplastic cells were pan-cytokeratin positive and vimentin negative. Additionally, nuclei immunoreactive to Ki-67 antigen were detected. Tumor cells were also negative to p53. Immunoreactivity to COX-2 was found in less than 10% of the neoplastic cells. No adjuvant therapies were instituted, and no evidence of local recurrence or distance metastasis was identified during the 24-month follow-up period

Expression Analysis of MicroRNAs in FFPE samples of canine cutaneous and oral melanoma by RT-qPCR

MicroRNA (miRNA), a class of small, non-coding RNA - regulating post-transcriptionally protein expression - are emerging as clinical biomarkers in many pathologies, including cancer [1]. Since miRNA are supposed to represent fundamental key regulators, better understanding of melanoma biology is essential to improve staging and therapy. The aim of the study was to investigate whether miRNA expression can vary in canine melanoma samples derived from formalin-fixed-paraffin-embedded (FFPE) tissues. Experimental design of the study included three groups, each one composed of 7 animals: i) control healthy skin group ii) oral melanoma group iii) skin melanoma group. The histhopatology and immunoistochemistry details of dogs included in the study are previously reported  [2]. Two tissue slides were used for miRNA extraction. The expression levels of seven miRNA - miR-145, miR-146a, miR-425-5p, miR-223, miR-365, miR-155 and miR-134 - were detected and assessed by qPCR using TaqMan® probes [3-5]. Five miRNA were significantly up-(n=3) or down-(n=2) regulated. In details, miR-146a and miR-155 abundance was increased as compared with control in both oral and skin melanoma (Fig 1 B,E) (p = 0.004 and 0.014 and p = 0.043 and 0.035 respectively), while the levels of miR-145 and miR-365 were lower (Fig 1 A,D) (p = 0.018 and 0.008 and p = 0.01 and 0.028, respectively). MiR-425-5p was upregulated (p = 0.039) only in skin melanoma (Fig. 1 C). Furthermore, functional analysis, carried out using miRNet web-based tool, showed that 76 genes related to cancer-associated pathways were possible target of these five microRNA (p = 6.95E-9); in particular, 21 target genes were associated with melanoma (p = 1.47E-5), including BRAF and CDK, E2F, FGF and PIK3 families. In conclusion, miR-145, miR-146a, miR-425-5p, miR-365 and miR-155 are differentially expressed in melanoma and healthy FFPE samples, suggesting that they may play a role in canine melanoma pathogenesis and/or progression

Trustworthiness of Laser-Induced Breakdown Spectroscopy Predictions via Simulation-based Synthetic Data Augmentation and Multitask Learning

We consider quantitative analyses of spectral data using laser-induced breakdown spectroscopy. We address the small size of training data available, and the validation of the predictions during inference on unknown data. For the purpose, we build robust calibration models using deep convolutional multitask learning architectures to predict the concentration of the analyte, alongside additional spectral information as auxiliary outputs. These secondary predictions can be used to validate the trustworthiness of the model by taking advantage of the mutual dependencies of the parameters of the multitask neural networks. Due to the experimental lack of training samples, we introduce a simulation-based data augmentation process to synthesise an arbitrary number of spectra, statistically representative of the experimental data. Given the nature of the deep learning model, no dimensionality reduction or data selection processes are required. The procedure is an end-to-end pipeline including the process of synthetic data augmentation, the construction of a suitable robust, homoscedastic, deep learning model, and the validation of its predictions. In the article, we compare the performance of the multitask model with traditional univariate and multivariate analyses, to highlight the separate contributions of each element introduced in the process.Comment: 35 pages, appendix with supplementary materia

Correlation between Tumour Associated Macrophage (TAM) Infiltration and Mitotic Activity in Canine Soft Tissue Sarcomas†

Tumour-associated macrophages (TAMs) are an important part of the tumour microenvironment but knowledge of their distribution in canine soft tissue sarcomas (STSs) is limited to absent. We analysed 38 STSs retrieved from the veterinary pathology archive; oral and visceral STSs, synovial cell sarcoma, tumours of histiocytic origin, haemangiosarcoma, carcinosarcomas, and undifferentiated tumours were excluded. Iba-1 positive, non-neoplastic tumour infiltrating cells (morphologically indicative of macrophages) were classified as TAMs and were counted in 10 consecutive tumours areas, where no necrosis or other inflammatory cells could be identified. Associations between numbers of TAMs and mitoses, differentiation, and necrosis scores or grade were investigated. TAMs were evident in all STSs and ranged between 6% to 62% of the cells in the microscopic field. The number of TAMs positively correlated with the STSs’ histologic grade. When the components of the grade were analysed separately, TAMs were statistically correlated with mitoses, but not with differentiation or necrosis score. The present findings suggest that TAMs are present in higher numbers when STS proliferation is the predominant feature that drives tumour grade. The abundant presence of TAMs in high-grade STSs may also increase the likelihood of a pathologist misdiagnosing STS for histiocytic sarcoma

MALASSEZIA, MITES AND BACTERIA IN THE EXTERNAL EAR CANAL OF DOGS AND CATS WITH OTITIS EXTERNA

Occurrence of Malassezia, mites and bacteria, was evaluated through cytology, culture and microscopical analysis of auricular cerumen collected from 115 cats and 203 dogs with otitis externa. For the dentification of Malassezia species, a PCR-based technique was also used. All the patients enrolled in the study were examined for Malassezia and all cats and 101 dogs were also investigated for mites. Bacteriological examination was performed on 16 cats and 60 dogs. The associations between Malassezia and the other pathogens and the correlations between Malassezia and season, gender and ear conformation, were evaluated. Malassezia pachydermatis was isolated from 58.2% cats and 52.7% dogs, while Otodectes cynotis was identified in 66.1% cats and in 5.9% dogs. Bacteria were detected in 18.7% cats and 36.7% dogs and Staphylococcus pseudointermedius, Staphylococcus epidermidis, Pseudomonas aeruginosa, Streptococcus canis, Escherichia coli and Bacillus sp. were identified. M. pachydermatis was isolated in pure culture from 28.3% cats and from 87.1% dogs, while it was associated with O. cynotis in 70.1% of cats and in 5% of dogs, and with bacteria in 1.5% of cats and 23.3% of dogs. Mixed infections caused by M. pachydermatis, bacteria (S. pseudointermedius) and mites occurred in 1 cat and 1 dog. Our results suggest that ear conformation is an important individual predisposing factor for Malassezia otitis in dogs and indicated the influence of the season on onset of Malassezia infections in cats