Genetic landscape of a large cohort of Primary Ovarian Insufficiency : New genes and pathways and implications for personalized medicine

Background Primary Ovarian Insufficiency (POI), a public health problem, affects 1-3.7% of women under 40 yield-ing infertility and a shorter lifespan. Most causes are unknown. Recently, genetic causes were identified, mostly in single families. We studied an unprecedented large cohort of POI to unravel its molecular pathophysiology.Methods 375 patients with 70 families were studied using targeted (88 genes) or whole exome sequencing with pathogenic/likely-pathogenic variant selection. Mitomycin-induced chromosome breakages were studied in patients' lymphocytes if necessary. Findings A high-yield of 29.3% supports a clinical genetic diagnosis of POI. In addition, we found strong evidence of pathogenicity for nine genes not previously related to a Mendelian phenotype or POI: ELAVL2, NLRP11, CENPE, SPATA33, CCDC150, CCDC185, including DNA repair genes: C17orf53(HROB), HELQ, SWI5 yielding high chromo-somal fragility. We confirmed the causal role of BRCA2, FANCM, BNC1, ERCC6, MSH4, BMPR1A, BMPR1B, BMPR2, ESR2, CAV1, SPIDR, RCBTB1 and ATG7 previously reported in isolated patients/families. In 8.5% of cases, POI is the only symptom of a multi-organ genetic disease. New pathways were identified: NF-kB, post-translational regulation, and mitophagy (mitochondrial autophagy), providing future therapeutic targets. Three new genes have been shown to affect the age of natural menopause supporting a genetic link.Interpretation We have developed high-performance genetic diagnostic of POI, dissecting the molecular pathogene-sis of POI and enabling personalized medicine to i) prevent/cure comorbidities for tumour/cancer susceptibility genes that could affect life-expectancy (37.4% of cases), or for genetically-revealed syndromic POI (8.5% of cases), ii) predict residual ovarian reserve (60.5% of cases). Genetic diagnosis could help to identify patients who may benefit from the promising in vitro activation-IVA technique in the near future, greatly improving its success in treating infertility.Funding Universite? Paris Saclay, Agence Nationale de Biome?decine.Copyright (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Peer reviewe

A novel approach for handedness detection from off-line handwriting using fuzzy conceptual reduction

A challenging area of pattern recognition is the recognition of handwritten texts in different languages and the reduction of a volume of data to the greatest extent while preserving associations (or dependencies) between objects of the original data. Until now, only a few studies have been carried out in the area of dimensionality reduction for handedness detection from off-line handwriting textual data. Nevertheless, further investigating new techniques to reduce the large amount of processed data in this field is worthwhile. In this paper, we demonstrate that it is important to select only the most characterizing features from handwritings and reject all those that do not contribute effectively to the process of handwriting recognition. To achieve this goal, the proposed approach is based mainly on fuzzy conceptual reduction by applying the Lukasiewicz implication. Handwritten texts in both Arabic and English languages are considered in this study. To evaluate the effectiveness of our proposal approach, classification is carried out using a K-Nearest-Neighbors (K-NN) classifier using a database of 121 writers. We consider left/right handedness as parameters for the evaluation where we determine the recall/precision and F-measure of each writer. Then, we apply dimensionality reduction based on fuzzy conceptual reduction by using the Lukasiewicz implication. Our novel feature reduction method achieves a maximum reduction rate of 83.43 %, thus making the testing phase much faster. The proposed fuzzy conceptual reduction algorithm is able to reduce the feature vector dimension by 31.3 % compared to the original "best of all combined features" algorithm.Qatar National Research Fund NPRP 09-864-1-128Scopu

Data Mining, Reasoning and Incremental Information Retrieval through Non Enlargeable Rectangular Relation Coverage

Association rules extraction from a binary relation as well as reasoning and information retrieval are generally based on the initial representation of the binary relation as an adjacency matrix. This presents some inconvenience in terms of space memory and knowledge organization. A coverage of a binary relation by a minimal number of non enlargeable rectangles generally reduces memory space consumption without any loss of information. It also has the advantage of organizing objects and attributes contained in the binary relation into a conceptual representation. In this paper, we propose new algorithms to extract association rules (i.e. data mining), conclusions from initial attributes (i.e. reasoning), as well as retrieving the total objects satisfying some initial attributes, by using only the minimal coverage. Finally we propose an incremental approximate algorithm to update a binary relation organized as a set of non enlargeable rectangles. Two main operations are mostly used during the organization process: First, separation of existing rectangles when we delete some pairs. Second, join of rectangles when common properties are discovered, after addition or removal of elements from a binary context. The objective is the minimization of the number of rectangles and the maximization of their structure. The article also raises the problems of equational modeling of the minimization criteria, as well as incrementally providing equations to maintain them

Using conceptual reasoning for inconsistencies detection in islamic advisory opinion (Fatwas)

The Islamic websites play an important role in disseminating Islamic knowledge and information about Islamic ruling. Their number and the content they provide is continuously increasing which require in-depth investigations in content evaluation automation. In this paper, we are proposing the use of conceptual reasoning for detecting inconsistencies in case of Fatwas evaluation. Inconsistencies are detected from propositional logic point-of-view based on Truth table binary relation.Scopu

Inconsistencies Detection In Islamic Texts Of Law Interpretations ["fatawas"]

Islamic web content offers a very convenient way for people to learn more about Islam religion and the correct practices. For instance, via these web sites they could ask for fatwas (Islamic advisory opinion) with more facilities and serenity. Regarding the sensitivity of the subject, large communities of researchers are working on the evaluation of these web sites according to several criteria. In particular there is a huge effort to check the consistency of the content with respect to the Islamic shariaa (or Islamic law). In this work we are proposing a semiautomatic approach for evaluating the web sites Islamic content, in terms of inconsistency detection, composed of the following steps: (i) Domain selection and definition: It consists of identifying the most relevant named entities related to the selected domain as well as their corresponding values or keywords (NEV). At that stage, we have started building the Fatwas ontology by analyzed around 100 fatwas extracted from the online system. (ii) Formal representation of the Islamic content: It consists of representing the content as formal context relating fatwas to NEV. Here, each named entity is split into different attributes in the database where each attribute is associated to a possible instantiation of the named entity. (iii) Rules extraction: by applying the ConImp tools, we extract a set of implications (or rules) reflecting cause-effect relations between NEV. As an extended option aiming to provide more precise analysis, we have proposed the inclusion of negative attributes. For example for word "licit", we may associate "not licit" or "forbidden", for word "recommended" we associated "not recommended", etc. At that stage by using an extension of Galois Connection we are able to find different logical associations in a minimal way by using the same tool ConImp. (iv) Conceptual reasoning: the objective is to detect a possibly inconsistency between the rules and evaluate their relevance. Each rule is mapped to a binary table in a relational database model. By joining obtained tables we are able to detect inconsistencies. We may also check if a new law is not contradicting existing set of laws by mapping the law into a logical expression. By creating a new table corresponding to its negation we have been able to prove automatically its consistencies as soon as we obtain an empty join of the total set of joins. This preliminary study showed that the logical representation of fatwas gives promising results in detecting inconsistencies within fatwa ontology. Future work includes using automatic named entity extraction and automatic transformation of law into a formatted database; we should be able to build a global system for inconsistencies detection for the domain.qscienc

A New Structural View Of The Holy Book Based On Specific Words: Towards Unique Chapters (surat) And Sentences (ayat) Characterization In The Quran

In the context of web Islamic data analysis and authentication an important task is to be able to authenticate the holy book if published in the net. For that purpose, in order to detect texts contained in the holy book, it seems obvious to first characterize words which are specific to existing chapters (i.e. "Sourat") and words characterizing each sentence in any chapter (i.e. "Aya"). In this current research, we have first mapped the text of the Quran to a binary context R linking each chapter to all words contained in it, and by calculating the fringe relation F of R, we have been able to discover in a very short time all specific words in each chapter of the holy book. By applying the same approach we have found all specific words of each sentence (i.e. "Aya") in the same chapter whenever it is possible. We have found that almost all sentences in the same chapter have one or many specific words. Only sentences repeated in the same chapter or those sentences included in each other might not have specific words. Observation of words simultaneously specific to a chapter in the holy book and to the sentence in the same chapter gave us the idea for characterizing all specific sentences in each chapter with respect to the whole Quran. We found that for 42 chapters all specific words of a chapter are also specific of some sentence in the same chapter. Such specific words might be used to detect in a shorter time website containing some part of the Quran and therefore should help for checking their authenticity. As a matter of fact by goggling only two or three specific words of a chapter, we observed that search results are directly related to the corresponding chapter in the Quran. Al results have been obtained for Arabic texts with or without vowels. Utilization of adequate data structures and threads enabled us to have efficient software written in Java language. The present tool is directly useful for the recognition of different texts in any domain. In the context of our current project, we project to use the same methods to characterize Islamic books in general.qscienc

A multi-level conceptual data reduction approach based on the Lukasiewicz implication

Starting from fuzzy binary data represented as tables in the fuzzy relational database, in this paper, we use fuzzy formal concept analysis to reduce the tables size to only keep the minimal rows in each table, without losing knowledge (i.e., association rules extracted from reduced databases are identical at given precision level). More specifically, we develop a fuzzy extension of a previously proposed algorithm for crisp data reduction without loss of knowledge. The fuzzy Galois connection based on the Lukasiewicz implication is mainly used in the definition of the closure operator according to a precision level, which makes data reduction sensitive to the variation of this precision level

Building multimedia repository for composing images perspective

Multimedia repository is helpful for educational activities since it offers several illustrations that facilitate the learning process and the text understanding. In this paper, we propose to build a multimedia repository from collected images using object extraction techniques. Then, we associate Arabic captions to all extracted objects. These extracted objects are used to compose new scenes that could illustrate efficiently the most important events in an Arabic story. We extend, thereby the notion of image composing to our approach as the task of constructing new images based on a set of toolboxes and a set of extracted objects as our multimedia repository of common animal behaviors. Our preliminary results show that the composed scenes using single objects provided a fair understanding of the main events of the stories as well as a coherent visual layout of all single objects. The diversity and the precision of the single objects images for the domain of animals have shown a great impact on composing new scenes either manually or dynamically.Other Information Published in: SN Applied Sciences License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1007/s42452-019-1123-y</p

ConProve: A conceptual prover system

ConProve is an automated prover for propositional logic. It takes, as an input, a set of propositional formulas and proves whether a goal holds or not. ConProve converts each formula to its corresponding Truth Table Binary Relation (TTBR) considered also as a formal context (FC). The objects in FC correspond to all possible formulas interpretations (in terms of their truth value assignments), and the properties in FC correspond to the terms. When the function the 'BuildContext' function, ConProve starts the new goal proving. Firstly, it adds the goal negation to the set of formulas and constructs the formal contexts (FCs) relating formulas to terms. Secondly, it makes the FCs grouping and deduces, based on the conceptual reasoning, if the goal holds. The tool offers a user-friendly interface allowing the editing of the set of formulas as well as the visualization of the reasoning steps. Besides the tool, the paper illustrates the importance of the conceptual reasoning in deriving new conclusions as well as in discovering new, possibly implications by applying the extended Galois Connection.Qatar National Research Fund NPRP 04-1109-1-174.Scopu