Have you forgotten? A method to assess if machine learning models have forgotten data

In the era of deep learning, aggregation of data from several sources is a common approach to ensuring data diversity. Let us consider a scenario where several providers contribute data to a consortium for the joint development of a classification model (hereafter the target model), but, now one of the providers decides to leave. This provider requests that their data (hereafter the query dataset) be removed from the databases but also that the model `forgets' their data. In this paper, for the first time, we want to address the challenging question of whether data have been forgotten by a model. We assume knowledge of the query dataset and the distribution of a model's output. We establish statistical methods that compare the target's outputs with outputs of models trained with different datasets. We evaluate our approach on several benchmark datasets (MNIST, CIFAR-10 and SVHN) and on a cardiac pathology diagnosis task using data from the Automated Cardiac Diagnosis Challenge (ACDC). We hope to encourage studies on what information a model retains and inspire extensions in more complex settings.Comment: Accepted by MICCAI 202

Accurate prediction of X-ray pulse properties from a free-electron laser using machine learning

Free-electron lasers providing ultra-short high-brightness pulses of X-ray radiation have great potential for a wide impact on science, and are a critical element for unravelling the structural dynamics of matter. To fully harness this potential, we must accurately know the X-ray properties: intensity, spectrum and temporal profile. Owing to the inherent fluctuations in free-electron lasers, this mandates a full characterization of the properties for each and every pulse. While diagnostics of these properties exist, they are often invasive and many cannot operate at a high-repetition rate. Here, we present a technique for circumventing this limitation. Employing a machine learning strategy, we can accurately predict X-ray properties for every shot using only parameters that are easily recorded at high-repetition rate, by training a model on a small set of fully diagnosed pulses. This opens the door to fully realizing the promise of next-generation high-repetition rate X-ray lasers

Adjuvant hysterectomy for treatment of residual disease in patients with cervical cancer treated with radiation therapy

The objective of this retrospective study was to determine the efficacy of adjuvant hysterectomy for treatment of residual disease in cervical carcinoma treated with radiation therapy. Between 1971 and 1996, 1590 patients with carcinoma of the uterine cervix (stages I–IIIb) were treated with radiation therapy. Three months after completion of radiation therapy, the status of local control was investigated, and total abdominal hysterectomy was performed in cases in which central residual disease existed in the cervix. Of the 1590 patients, residual disease was identified in 162 patients. Among these patients, 35 showed an absence of distant metastasis or lateral parametrial invasion and underwent hysterectomy. The overall 5- and 10-year survival rates for these patients were 68.6 and 65.7%, respectively. There was no significant difference in survival between patients with squamous cell carcinoma and those with non-squamous cell carcinoma or between patients with stage I/II carcinoma and those with stage III carcinoma. With respect to treatment-related morbidity, five (14.3%) patients suffered grade III or IV complications after hysterectomy. Adjuvant hysterectomy is an effective addition to radiation therapy in the treatment of cervical cancer, even in patients with stage III disease and in those with non-squamous cell carcinoma

Heavy and light roles: myosin in the morphogenesis of the heart

Myosin is an essential component of cardiac muscle, from the onset of cardiogenesis through to the adult heart. Although traditionally known for its role in energy transduction and force development, recent studies suggest that both myosin heavy-chain and myosin lightchain proteins are required for a correctly formed heart. Myosins are structural proteins that are not only expressed from early stages of heart development, but when mutated in humans they may give rise to congenital heart defects. This review will discuss the roles of myosin, specifically with regards to the developing heart. The expression of each myosin protein will be described, and the effects that altering expression has on the heart in embryogenesis in different animal models will be discussed. The human molecular genetics of the myosins will also be reviewed

Mathematical Modelling of Cell-Fate Decision in Response to Death Receptor Engagement

Cytokines such as TNF and FASL can trigger death or survival depending on cell lines and cellular conditions. The mechanistic details of how a cell chooses among these cell fates are still unclear. The understanding of these processes is important since they are altered in many diseases, including cancer and AIDS. Using a discrete modelling formalism, we present a mathematical model of cell fate decision recapitulating and integrating the most consistent facts extracted from the literature. This model provides a generic high-level view of the interplays between NFκB pro-survival pathway, RIP1-dependent necrosis, and the apoptosis pathway in response to death receptor-mediated signals. Wild type simulations demonstrate robust segregation of cellular responses to receptor engagement. Model simulations recapitulate documented phenotypes of protein knockdowns and enable the prediction of the effects of novel knockdowns. In silico experiments simulate the outcomes following ligand removal at different stages, and suggest experimental approaches to further validate and specialise the model for particular cell types. We also propose a reduced conceptual model implementing the logic of the decision process. This analysis gives specific predictions regarding cross-talks between the three pathways, as well as the transient role of RIP1 protein in necrosis, and confirms the phenotypes of novel perturbations. Our wild type and mutant simulations provide novel insights to restore apoptosis in defective cells. The model analysis expands our understanding of how cell fate decision is made. Moreover, our current model can be used to assess contradictory or controversial data from the literature. Ultimately, it constitutes a valuable reasoning tool to delineate novel experiments

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches

IntroductionThe COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. MethodsExtensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors.ResultsResults revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DiscussionThe key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies

Xist-dependent imprinted X inactivation and the early developmental consequences of its failure

The long noncoding RNA Xist is expressed from only the paternal X chromosome in mouse preimplantation female embryos and mediates transcriptional silencing of that chromosome. In females, absence of Xist leads to postimplantation lethality. Here, through single-cell RNA sequencing of early preimplantation mouse embryos, we found that the initiation of imprinted X-chromosome inactivation absolutely requires Xist. Lack of paternal Xist leads to genome-wide transcriptional misregulation in the early blastocyst and to failure to activate the extraembryonic pathway that is essential for postimplantation development. We also demonstrate that the expression dynamics of X-linked genes depends on the strain and parent of origin as well as on the location along the X chromosome, particularly at the first 'entry' sites of Xist. This study demonstrates that dosage-compensation failure has an effect as early as the blastocyst stage and reveals genetic and epigenetic contributions to orchestrating transcriptional silencing of the X chromosome during early embryogenesis.This work was funded by a fellowship of Région Ile-de-France (DIM STEMP OLE) to M.B., the Paris Alliance of Cancer Research Institutes (PACRI-ANR) to LS and ERC Advanced Investigator award (ERC-2010-AdG–No.250367), EU FP7 grants SYBOSS (EU 7th Framework G.A. no. 242129) and MODHEP (EU 7th Framework G.A. no. 259743), La Ligue, Fondation de France, Labex DEEP (ANR-11-LBX-0044) part of the IDEX Idex PSL (ANR-10-IDEX-0001-02 PSL) and ABS4NGS (ANR-11-BINF-0001) to E.H and France Genomique National infrastructure (ANR-10-INBS09) to EH, NS, EB

Ecological strategy for soil contaminated with mercury

Aims The paper presents results from plot experiments aimed at the development of an ecological strategy for soil contaminated with mercury. Meadow grass (Poa pratensis) was tested on mercury contaminated soil in a former chlor-alkali plant (CAP) in southern Poland for its phytoremediation potential. Methods The stabilisation potential of the plants was investigated on plots without additives and after the addition of granular sulphur. Biomass production, uptake and distribution of mercury by plants, as well as leachates and rhizosphere microorganisms were investigated, along with the growth and vitality of plants during one growing season. Results The analysed plants grew easily on mercury contaminated soil, accumulating lower amounts of mercury, especially in the roots, from soil with additive of granular sulphur (0.5 % w/w) and sustained a rich microbial population in the rhizosphere. After amendment application the reduction of Hg evaporation was observed. Conclusions The obtained results demonstrate the potential of using Poa pratensis and sulphur for remediation of mercury contaminated soil and reduction of the Hg evaporation from soil. In the presented study, methods of Hg reduction on “hot spots” were proposed, with a special focus on environmental protection. This approach provides a simple remediation tool for large areas heavily contaminated with mercury