Heuristic search of (semi-)bent functions based on cellular automata

An interesting thread in the research of Boolean functions for cryptography and coding theory is the study of secondary constructions: given a known function with a good cryptographic profile, the aim is to extend it to a (usually larger) function possessing analogous properties. In this work, we continue the investigation of a secondary construction based on cellular automata (CA), focusing on the classes of bent and semi-bent functions. We prove that our construction preserves the algebraic degree of the local rule, and we narrow our attention to the subclass of quadratic functions, performing several experiments based on exhaustive combinatorial search and heuristic optimization through Evolutionary Strategies (ES). Finally, we classify the obtained results up to permutation equivalence, remarking that the number of equivalence classes that our CA-XOR construction can successfully extend grows very quickly with respect to the CA diameter

99pharnessing copper in cancer to enhance anti tumor immune response

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Carbon Nanohorns as Effective Nanotherapeutics in Cancer Therapy

Different carbon nanostructures have been explored as functional materials for the development of effective nanomaterials in cancer treatment applications. This review mainly aims to discuss the features, either strength or weakness, of carbon nanohorn (CNH), carbon conical horn-shaped nanostructures of sp2 carbon atoms. The interest for these materials arises from their ability to couple the clinically relevant properties of carbon nanomaterials as drug carriers with the negligible toxicity described in vivo. Here, we offer a comprehensive overview of the recent advances in the use of CNH in cancer treatments, underlining the benefits of each functionalization route and approach, as well as the biological performances of either loaded and unloaded materials, while discussing the importance of delivery devices

The Relationship Between Intermittent Limit Cycles and Postural Instability Associated with Parkinson’s Disease

Background: Many disease-specifc factors such as muscular weakness, increased muscle stiffness, varying postural strategies, and changes in postural refexes have been shown to lead to postural instability and fall risk in people with Parkinson’s disease (PD). Recently, analytical techniques, inspired by the dynamical systems perspective on movement control and coordination, have been used to examine the mechanisms underlying the dynamics of postural declines and the emergence of postural instabilities in people with PD. Methods: A wavelet-based technique was used to identify limit cycle oscillations (LCOs) in the anterior–posterior (AP) postural sway of people with mild PD (n = 10) compared to age-matched controls (n = 10). Participants stood on a foam and on a rigid surface while completing a dual task (speaking). Results: There was no signifcant difference in the root mean square of center of pressure between groups. Three out of 10 participants with PD demonstrated LCOs on the foam surface, while none in the control group demonstrated LCOs. An inverted pendulum model of bipedal stance was used to demonstrate that LCOs occur due to disease-specifc changes associated with PD: time-delay and neuromuscular feedback gain. Conclusion: Overall, the LCO analysis and mathematical model appear to capture the subtle postural instabilities associated with mild PD. In addition, these fndings provide insights into the mechanisms that lead to the emergence of unstable posture in patients with PD

Iron depletion suppresses mTORC1-directed signalling in intestinal Caco-2 cells via induction of REDD

Acknowledgements This work was supported by grants from the Biotechnology and Biological Science Research Council (BB/I007261/1 and BB/N002342/1) and The Scottish Government's Rural and Environment Science and Analytical Services Division (RESAS 854/11).Peer reviewedPublisher PD

Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge

Automatic detection of pulmonary nodules in thoracic computed tomography (CT) scans has been an active area of research for the last two decades. However, there have only been few studies that provide a comparative performance evaluation of different systems on a common database. We have therefore set up the LUNA16 challenge, an objective evaluation framework for automatic nodule detection algorithms using the largest publicly available reference database of chest CT scans, the LIDC-IDRI data set. In LUNA16, participants develop their algorithm and upload their predictions on 888 CT scans in one of the two tracks: 1) the complete nodule detection track where a complete CAD system should be developed, or 2) the false positive reduction track where a provided set of nodule candidates should be classified. This paper describes the setup of LUNA16 and presents the results of the challenge so far. Moreover, the impact of combining individual systems on the detection performance was also investigated. It was observed that the leading solutions employed convolutional networks and used the provided set of nodule candidates. The combination of these solutions achieved an excellent sensitivity of over 95% at fewer than 1.0 false positives per scan. This highlights the potential of combining algorithms to improve the detection performance. Our observer study with four expert readers has shown that the best system detects nodules that were missed by expert readers who originally annotated the LIDC-IDRI data. We released this set of additional nodules for further development of CAD systems

Borgese, Salvemini, La Piana e "le systeme de l'exil"

L'articolo ricostruisce la trama dei rapporti intellettuali e politici tra tre grandi esuli: Borgede, Salvemini e La Pian

A novel transcriptional signature identifies T-cell infiltration in high-risk paediatric cancer.

BACKGROUND: Molecular profiling of the tumour immune microenvironment (TIME) has enabled the rational choice of immunotherapies in some adult cancers. In contrast, the TIME of paediatric cancers is relatively unexplored. We speculated that a more refined appreciation of the TIME in childhood cancers, rather than a reliance on commonly used biomarkers such as tumour mutation burden (TMB), neoantigen load and PD-L1 expression, is an essential prerequisite for improved immunotherapies in childhood solid cancers. METHODS: We combined immunohistochemistry (IHC) with RNA sequencing and whole-genome sequencing across a diverse spectrum of high-risk paediatric cancers to develop an alternative, expression-based signature associated with CD8+ T-cell infiltration of the TIME. Furthermore, we explored transcriptional features of immune archetypes and T-cell receptor sequencing diversity, assessed the relationship between CD8+ and CD4+ abundance by IHC and deconvolution predictions and assessed the common adult biomarkers such as neoantigen load and TMB. RESULTS: A novel 15-gene immune signature, Immune Paediatric Signature Score (IPASS), was identified. Using this signature, we estimate up to 31% of high-risk cancers harbour infiltrating T-cells. In addition, we showed that PD-L1 protein expression is poorly correlated with PD-L1 RNA expression and TMB and neoantigen load are not predictive of T-cell infiltration in paediatrics. Furthermore, deconvolution algorithms are only weakly correlated with IHC measurements of T-cells. CONCLUSIONS: Our data provides new insights into the variable immune-suppressive mechanisms dampening responses in paediatric solid cancers. Effective immune-based interventions in high-risk paediatric cancer will require individualised analysis of the TIME.Chelsea Mayoh, Andrew J. Gifford, Rachael Terry, Loretta M. S. Lau, Marie Wong, Padmashree Rao, Tyler Shai, Hee, Federica Saletta, Dong, Anh Khuong, Quang, Vicky Qin, Marion K. Mateos, Deborah Meyran, Katherine E. Miller, Aysen Yuksel, Emily V. A. Mould, Rachel Bowen, James, Dinisha Govender, Akanksha Senapati, Nataliya Zhukova, Natacha Omer, Hetal Dholaria, Frank Alvaro, Heather Tapp, Yonatan Diamond, Luciano Dalla Pozza, Andrew S. Moore, Wayne Nicholls, Nicholas G. Gottardo, Geoffrey McCowage, Jordan R. Hansford, Seong, Lin Khaw, Paul J. Wood, Daniel Catchpoole, Catherine E. Cottrell, Elaine R. Mardis, Glenn M. Marshall, Vanessa Tyrrell, Michelle Haber, David S. Ziegler, Orazio Vittorio, Joseph A. Trapani, Mark J. Cowley, Paul J. Neeson, and Paul G. Eker