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Homologous recombination deficiency (HRD) is a key biomarker associated with increased sensitivity to PARP inhibitors (PARPi) in advanced epithelial ovarian cancer. Accurate identification of HRD status is essential for selecting patients most likely to benefit from these therapies. Current diagnostic approaches combine sequencing to detect mutations in homologous recombination repair genes—particularly BRCA1 and BRCA2—with genome-wide analysis of structural genomic alterations indicative of HRD. This review briefly outlines the biological basis of HRD and its clinical significance and then focuses on currently available assays for HRD assessment. We compare their molecular strategies, including the use of targeted gene panels and genomic instability metrics such as loss of heterozygosity, telomeric allelic imbalance, and large-scale state transitions. The review also highlights the strengths and limitations of each platform and discusses their role in guiding clinical decision-making. Challenges related to dynamic tumor evolution and the interpretation of HRD status in recurrent disease settings are also addressed.

We report on the characterization of NbTi films at ∼ 11 GHz and in DC magnetic fields up to 4 T, performed by means of the coplanar waveguide resonator technique, providing quantitative information about the penetration depth, the complex impedance, and the vortex-motion-induced complex resistivity. This kind of characterization is essential for the development of radiofrequency cavity technology. To access the vortex-pinning parameters, the complex impedance was analyzed within the formalism of the Campbell penetration depth. Measurements in this frequency range allowed us to determine the complete set of vortex-pinning parameters and the flux flow resistivity, both analyzed and discussed in the framework of high-frequency vortex dynamics models. The analysis also benefits from the comparison with results obtained by a dielectric-loaded resonator technique on similar samples and by other ancillary structural and electromagnetic characterization techniques that provide us with a comprehensive picture of the material. It turns out that the normalized flux flow resistivity follows remarkably well the trend predicted by the time dependent Ginzburg-Landau theory, while the pinning constant exhibits a decreasing trend with the field which points to a collective pinning regime.

Background Spontaneous tumors in dog have been demonstrated to share many features with their human counterparts, including relevant molecular targets, histological appearance, genetics, biological behavior and response to conventional treatments. Mammary tumors in dog therefore provide an attractive alternative to more classical mouse models, such as transgenics or xenografts, where the tumour is artificially induced. To assess the extent to which dog tumors represent clinically significant human phenotypes, we performed the first genome-wide comparative analysis of transcriptional changes occurring in mammary tumors of the two species, with particular focus on the molecular pathways involved. Results We analyzed human and dog gene expression data derived from both tumor and normal mammary samples. By analyzing the expression levels of about ten thousand dog/human orthologous genes we observed a significant overlap of genes deregulated in the mammary tumor samples, as compared to their normal counterparts. Pathway analysis of gene expression data revealed a great degree of similarity in the perturbation of many cancer-related pathways, including the 'PI3K/AKT', 'KRAS', 'PTEN', 'WNT-beta catenin' and 'MAPK cascade'. Moreover, we show that the transcriptional relationships between different gene signatures observed in human breast cancer are largely maintained in the canine model, suggesting a close interspecies similarity in the network of cancer signalling circuitries. Conclusion Our data confirm and further strengthen the value of the canine mammary cancer model and open up new perspectives for the evaluation of novel cancer therapeutics and the development of prognostic and diagnostic biomarkers to be used in clinical studies.

Abstract Mesenteric vein thrombosis (MVT) is a rare condition, often misdiagnosed due to its vague and misleading clinical presentation. It can cause intestinal infarction, peritonitis, and consequently necessitate bowel resection. CT scanning with intravenous contrast enhancement is the gold standard for its diagnosis. Radiologists have an important role in defining the extent of thrombosis and identifying any signs of intestinal infarction influencing the decision whether or not to operate. In patients with no clinical signs of peritonitis or radiological evidence of intestinal infarction, the treatment can be exclusively medical, based on full anticoagulation (initially with low molecular weight heparin, followed by vitamin K antagonists or direct acting oral-anticoagulants). The duration of medical treatment depends on radiological evidence of resolution of thrombosis and the identification of pro-coagulant risk factors.

Concept Bottleneck Models (CBMs) are neural networks designed to conjoin high performance with ante-hoc interpretability. CBMs work by first mapping inputs (e.g., images) to high-level concepts (e.g., visible objects and their properties) and then use these to solve a downstream task (e.g., tagging or scoring an image) in an interpretable manner. Their performance and interpretability, however, hinge on the quality of the concepts they learn. The go-to strategy for ensuring good quality concepts is to leverage expert annotations, which are expensive to collect and seldom available in applications. Researchers have recently addressed this issue by introducing \"VLM-CBM\" architectures that replace manual annotations with weak supervision from foundation models. It is however unclear what is the impact of doing so on the quality of the learned concepts. To answer this question, we put state-of-the-art VLM-CBMs to the test, analyzing their learned concepts empirically using a selection of significant metrics. Our results show that, depending on the task, VLM supervision can sensibly differ from expert annotations, and that concept accuracy and quality are not strongly correlated. Our code is available at https://github.com/debryu/CQA.

In this work, microwave measurements carried out in dielectric-loaded resonators exposed to high magnetic fields are exploited to yield the surface impedance of Nb\\(_3\\)Sn superconducting coatings deposited via two different techniques: vapor tin diffusion, and DC magnetron sputtering. The obtained data lead to qualitative interpretations on both the Nb\\(_3\\)Sn superconducting properties, and vortex-dynamics and pinning, of each coating separately, as well as simple distinctive features when comparing those. When examining the respective surface impedances at varying field, it is expected that the studied films perform at substantially diverse magnitudes of flux-flow resistivity, but also in well-differentiated pinning regimes, yet the obtained surface resistances of both samples are comparable, thus demonstrating that there is room for film optimization at the expense of certain compromise between the parameters involved.