Cohomology of the Lie Superalgebra of Contact Vector Fields on R1∣1\mathbb{R}^{1|1} and Deformations of the Superspace of Symbols

Following Feigin and Fuchs, we compute the first cohomology of the Lie superalgebra $\mathcal{K}(1)$ of contact vector fields on the (1,1)-dimensional real superspace with coefficients in the superspace of linear differential operators acting on the superspaces of weighted densities. We also compute the same, but $\mathfrak{osp}(1|2)$-relative, cohomology. We explicitly give 1-cocycles spanning these cohomology. We classify generic formal $\mathfrak{osp}(1|2)$-trivial deformations of the $\mathcal{K}(1)$-module structure on the superspaces of symbols of differential operators. We prove that any generic formal $\mathfrak{osp}(1|2)$-trivial deformation of this $\mathcal{K}(1)$-module is equivalent to a polynomial one of degree $\leq4$. This work is the simplest superization of a result by Bouarroudj [On $\mathfrak{sl}$(2)-relative cohomology of the Lie algebra of vector fields and differential operators, J. Nonlinear Math. Phys., no.1, (2007), 112--127]. Further superizations correspond to $\mathfrak{osp}(N|2)$-relative cohomology of the Lie superalgebras of contact vector fields on $1|N$-dimensional superspace

Computer-Assisted Classification Patterns in Autoimmune Diagnostics: The AIDA Project

Antinuclear antibodies (ANAs) are significant biomarkers in the diagnosis of autoimmune diseases in humans, done by mean of Indirect ImmunoFluorescence (IIF)method, and performed by analyzing patterns and fluorescence intensity. This paper introduces the AIDA Project (autoimmunity: diagnosis assisted by computer) developed in the framework of an Italy-Tunisia cross-border cooperation and its preliminary results. A database of interpreted IIF images is being collected through the exchange of images and double reporting and a Gold Standard database, containing around 1000 double reported images, has been settled. The Gold Standard database is used for optimization of aCAD(Computer AidedDetection) solution and for the assessment of its added value, in order to be applied along with an Immunologist as a second Reader in detection of autoantibodies. This CAD system is able to identify on IIF images the fluorescence intensity and the fluorescence pattern. Preliminary results show that CAD, used as second Reader, appeared to perform better than Junior Immunologists and hence may significantly improve their efficacy; compared with two Junior Immunologists, the CAD system showed higher Intensity Accuracy (85,5% versus 66,0% and 66,0%), higher Patterns Accuracy (79,3% versus 48,0% and 66,2%), and higher Mean Class Accuracy (79,4% versus 56,7% and 64.2%)

Preliminary results of the project A.I.D.A. (Auto Immunity: Diagnosis Assisted by computer)

In this paper, are presented the preliminary results of the A.I.D.A. (Auto Immunity: Diagnosis Assisted by computer) project which is developed in the frame of the cross-border cooperation Italy-Tunisia. According to the main objectives of this project, a database of interpreted Indirect ImmunoFluorescence (IIF) images on HEp 2 cells is being collected thanks to the contribution of Italian and Tunisian experts involved in routine diagnosis of autoimmune diseases. Through exchanging images and double reporting; a Gold Standard database, containing around 1000 double reported IIF images with different patterns including negative tests, has been settled. This Gold Standard database has been used for optimization of a computing solution (CADComputer Aided Detection) and for assessment of its added value in order to be used along with an immunologist as a second reader in detection of auto antibodies for autoimmune disease diagnosis. From the preliminary results obtained, the CAD appeared more powerful than junior immunologists used as second readers and may significantly improve their efficacy

An “Electronic Fluorescent Pictograph” Browser for Exploring and Analyzing Large-Scale Biological Data Sets

Background. The exploration of microarray data and data from other high-throughput projects for hypothesis generation has become a vital aspect of post-genomic research. For the non-bioinformatics specialist, however, many of the currently available tools provide overwhelming amounts of data that are presented in a non-intuitive way. Methodology/Principal Findings. In order to facilitate the interpretation and analysis of microarray data and data from other large-scale data sets, we have developed a tool, which we have dubbed the electronic Fluorescent Pictograph – or eFP – Browser, available a

Hereditary breast cancer in Middle Eastern and North African (MENA) populations: identification of novel, recurrent and founder BRCA1 mutations in the Tunisian population

Germ-line mutations in BRCA1 breast cancer susceptibility gene account for a large proportion of hereditary breast cancer families and show considerable ethnic and geographical variations. The contribution of BRCA1 mutations to hereditary breast cancer has not yet been thoroughly investigated in Middle Eastern and North African populations. In this study, 16 Tunisian high-risk breast cancer families were screened for germline mutations in the entire BRCA1 coding region and exon–intron boundaries using direct sequencing. Six families were found to carry BRCA1 mutations with a prevalence of 37.5%. Four different deleterious mutations were detected. Three truncating mutations were previously described: c.798_799delTT (916 delTT), c.3331_3334delCAAG (3450 delCAAG), c.5266dupC (5382 insC) and one splice site mutation which seems to be specific to the Tunisian population: c.212 + 2insG (IVS5 + 2insG). We also identified 15 variants of unknown clinical significance. The c.798_799delTT mutation occurred at an 18% frequency and was shared by three apparently unrelated families. Analyzing five microsatellite markers in and flanking the BRCA1 locus showed a common haplotype associated with this mutation. This suggests that the c.798_799delTT mutation is a Tunisian founder mutation. Our findings indicate that the Tunisian population has a spectrum of prevalent BRCA1 mutations, some of which appear as recurrent and founding mutations

Measurement of the ratio of branching fractions BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma) and the direct CP asymmetry in B0 -> K*0 gamma

The ratio of branching fractions of the radiative B decays B0 -> K*0 gamma and Bs0 phi gamma has been measured using an integrated luminosity of 1.0 fb-1 of pp collision data collected by the LHCb experiment at a centre-of-mass energy of sqrt(s)=7 TeV. The value obtained is BR(B0 -> K*0 gamma)/BR(Bs0 -> phi gamma) = 1.23 +/- 0.06(stat.) +/- 0.04(syst.) +/- 0.10(fs/fd), where the first uncertainty is statistical, the second is the experimental systematic uncertainty and the third is associated with the ratio of fragmentation fractions fs/fd. Using the world average value for BR(B0 -> K*0 gamma), the branching fraction BR(Bs0 -> phi gamma) is measured to be (3.5 +/- 0.4) x 10^{-5}. The direct CP asymmetry in B0 -> K*0 gamma decays has also been measured with the same data and found to be A(CP)(B0 -> K*0 gamma) = (0.8 +/- 1.7(stat.) +/- 0.9(syst.))%. Both measurements are the most precise to date and are in agreement with the previous experimental results and theoretical expectations.Comment: 21 pages, 3 figues, 4 table

Unpublished Mediterranean and Black Sea records of marine alien, cryptogenic, and neonative species

To enrich spatio-temporal information on the distribution of alien, cryptogenic, and neonative species in the Mediterranean and the Black Sea, a collective effort by 173 marine scientists was made to provide unpublished records and make them open access to the scientific community. Through this effort, we collected and harmonized a dataset of 12,649 records. It includes 247 taxa, of which 217 are Animalia, 25 Plantae and 5 Chromista, from 23 countries surrounding the Mediterranean and the Black Sea. Chordata was the most abundant taxonomic group, followed by Arthropoda, Mollusca, and Annelida. In terms of species records, Siganus luridus, Siganus rivulatus, Saurida lessepsianus, Pterois miles, Upeneus moluccensis, Charybdis (Archias) longicollis, and Caulerpa cylindracea were the most numerous. The temporal distribution of the records ranges from 1973 to 2022, with 44% of the records in 2020–2021. Lethrinus borbonicus is reported for the first time in the Mediterranean Sea, while Pomatoschistus quagga, Caulerpa cylindracea, Grateloupia turuturu, and Misophria pallida are first records for the Black Sea; Kapraunia schneideri is recorded for the second time in the Mediterranean and for the first time in Israel; Prionospio depauperata and Pseudonereis anomala are reported for the first time from the Sea of Marmara. Many first country records are also included, namely: Amathia verticillata (Montenegro), Ampithoe valida (Italy), Antithamnion amphigeneum (Greece), Clavelina oblonga (Tunisia and Slovenia), Dendostrea cf. folium (Syria), Epinephelus fasciatus (Tunisia), Ganonema farinosum (Montenegro), Macrorhynchia philippina (Tunisia), Marenzelleria neglecta (Romania), Paratapes textilis (Tunisia), and Botrylloides diegensis (Tunisia)

Future-ai:International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI