Completeness and decidability results for hybrid(ised) logics

Adding to the modal description of transition structures the ability to refer to specific states, hybrid(ised) logics provide an interesting framework for the specification of reconfigurable systems. The qualifier ‘hybrid(ised)’ refers to a generic method of developing, on top of whatever specification logic is used to model software configurations, the elements of an hybrid language, including nominals and modalities. In such a context, this paper shows how a calculus for a hybrid(ised) logic can be generated from a calculus of the base logic and that, moreover, it preserves soundness and completeness. A second contribution establishes that hybridising a decidable logic also gives rise to a decidable hybrid(ised) one. These results pave the way to the development of dedicated proof tools for such logics used in the design of reconfigurable systems

Asymmetric Combination of Logics is Functorial: A Survey

Asymmetric combination of logics is a formal process that develops the characteristic features of a specific logic on top of another one. Typical examples include the development of temporal, hybrid, and probabilistic dimensions over a given base logic. These examples are surveyed in the paper under a particular perspective—that this sort of combination of logics possesses a functorial nature. Such a view gives rise to several interesting questions. They range from the problem of combining translations (between logics), to that of ensuring property preservation along the process, and the way different asymmetric combinations can be related through appropriate natural transformations

Case report: Rare skeletal manifestations in a child with primary hyperparathyroidism

Background: Primary hyperparathyroidism (PHPT) is uncommon among children with an incidence of 1:300,000. This diagnosis is often missed in children in contrast to adults where it is detected at a pre symptomatic stage due to routine blood investigations. Etiology of PHPT can be due to adenoma, hyperplasia or rarely carcinoma. Case presentation: A 12year old Sri Lankan girl presented with progressive difficulty in walking since 1year. On examination she had bilateral genu valgum. Skeletal survey revealed valgus deformity of knee joints, bilateral subluxation of upper femoral epiphysis(SUFE), epiphyseal displacement of bilateral humeri, rugger jersey spine and subperiosteal bone resorptions in lateral aspects of 2nd and 3rd middle phalanges. There were no radiological manifestations of rickets. Metabolic profile revealed hypercalcemia with hypophosphatemia. Intact parathyroid hormone levels were elevated at 790pg/ml. Vitamin D levels were deficient. She had low bone mineral density with Z score of -3.4. Vitamin D supplementation resulted in worsening of hypercalcemia without reduction in PTH levels. Tc 99 Sestamibi uptake scan showed abnormal tracer retention in left inferior pole of thyroid. A large parathyroid gland was removed with histology favoring parathyroid adenoma. Post operatively she developed hypocalcemia. Bilateral osteotomy was done for SUFE and further surgeries for correction of limb deformities planned. Conclusion: PHPT in children is usually diagnosed late when irreversible organ damage has occurred. Children can present with non specific symptoms involving gastrointestinal, musculoskeletal, renal and neurological systems. PHPT can cause disarray in bone and epiphysis in children during pubertal growth spurt. Genu valgum and SUFE are rare skeletal manifestations in PHPT and only 10 cases of genu valgum and 9 cases of SUFE have been reported up to now. So far no cases have been reported on epiphyseal displacement of humeri. Awareness regarding the occurrence of these rare skeletal manifestations especially during puberty is important for early diagnosis to prevent irreversible outcomes

Evaluation of urinary cysteinyl leukotrienes as biomarkers of severity and putative therapeutic targets in COVID-19 patients

Background Cysteinyl leukotrienes (CysLT) are potent inflammation-promoting mediators, but remain scarcely explored in COVID-19. We evaluated urinary CysLT (U-CysLT) relationship with disease severity and their usefulness for prognostication in hospitalized COVID-19 patients. The impact on U-CysLT of veno-venous extracorporeal membrane oxygenation (VV-ECMO) and of comorbidities such as hypertension and obesity was also assessed. Methods Blood and spot urine were collected in severe (n = 26), critically ill (n = 17) and critically ill on VV-ECMO (n = 17) patients with COVID-19 at days 1-2 (admission), 3-4, 5-8 and weekly thereafter, and in controls (n = 23) at a single time point. U-CysLT were measured by ELISA. Routine markers, prognostic scores and outcomes were also evaluated. Results U-CysLT did not differ between groups at admission, but significantly increased along hospitalization only in critical groups, being markedly higher in VV-ECMO patients, especially in hypertensives. U-CysLT values during the first week were positively associated with ICU and total hospital length of stay in critical groups and showed acceptable area under curve (AUC) for prediction of 30-day mortality (AUC: 0.734, p = 0.001) among all patients. Conclusions U-CysLT increase during hospitalization in critical COVID-19 patients, especially in hypertensives on VV-ECMO. U-CysLT association with severe outcomes suggests their usefulness for prognostication and as therapeutic targets.This work was supported by a RESEARCH 4 COVID-19 grant (project 519, reference number: 613690173) from FCT-Fundacao para a Ciencia e a Tecnologia (special support for rapid implementation projects for innovative response solutions to COVID-9 pandemic). CS-P is a recipient of a Ph.D. fellowship from FCT and MedInUP (UI/BD/150816/2020). P-PT was supported by a research contract within the scope of the RIFF-HEART project funded by FEDER via COMPETE, Portugal 2020-Operational Programme for Competitiveness and Internationalization (POCI) (POCI-01-0145-FEDER-032188) and by FCT (PTDC/MEC-CAR/32188/2017). Open access funding provided by FCT|FCCN (b-on)

Discovering study-specific gene regulatory networks

This article has been made available through the Brunel Open Access Publishing Fund.Microarrays are commonly used in biology because of their ability to simultaneously measure thousands of genes under different conditions. Due to their structure, typically containing a high amount of variables but far fewer samples, scalable network analysis techniques are often employed. In particular, consensus approaches have been recently used that combine multiple microarray studies in order to find networks that are more robust. The purpose of this paper, however, is to combine multiple microarray studies to automatically identify subnetworks that are distinctive to specific experimental conditions rather than common to them all. To better understand key regulatory mechanisms and how they change under different conditions, we derive unique networks from multiple independent networks built using glasso which goes beyond standard correlations. This involves calculating cluster prediction accuracies to detect the most predictive genes for a specific set of conditions. We differentiate between accuracies calculated using cross-validation within a selected cluster of studies (the intra prediction accuracy) and those calculated on a set of independent studies belonging to different study clusters (inter prediction accuracy). Finally, we compare our method's results to related state-of-the art techniques. We explore how the proposed pipeline performs on both synthetic data and real data (wheat and Fusarium). Our results show that subnetworks can be identified reliably that are specific to subsets of studies and that these networks reflect key mechanisms that are fundamental to the experimental conditions in each of those subsets

DeBi: Discovering Differentially Expressed Biclusters using a Frequent Itemset Approach

<p>Abstract</p> <p>Background</p> <p>The analysis of massive high throughput data via clustering algorithms is very important for elucidating gene functions in biological systems. However, traditional clustering methods have several drawbacks. Biclustering overcomes these limitations by grouping genes and samples simultaneously. It discovers subsets of genes that are co-expressed in certain samples. Recent studies showed that biclustering has a great potential in detecting marker genes that are associated with certain tissues or diseases. Several biclustering algorithms have been proposed. However, it is still a challenge to find biclusters that are significant based on biological validation measures. Besides that, there is a need for a biclustering algorithm that is capable of analyzing very large datasets in reasonable time.</p> <p>Results</p> <p>Here we present a fast biclustering algorithm called DeBi (Differentially Expressed BIclusters). The algorithm is based on a well known data mining approach called frequent itemset. It discovers maximum size homogeneous biclusters in which each gene is strongly associated with a subset of samples. We evaluate the performance of DeBi on a yeast dataset, on synthetic datasets and on human datasets.</p> <p>Conclusions</p> <p>We demonstrate that the DeBi algorithm provides functionally more coherent gene sets compared to standard clustering or biclustering algorithms using biological validation measures such as Gene Ontology term and Transcription Factor Binding Site enrichment. We show that DeBi is a computationally efficient and powerful tool in analyzing large datasets. The method is also applicable on multiple gene expression datasets coming from different labs or platforms.</p

A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data

<p>Abstract</p> <p>Background</p> <p>In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of rows coherent with groups of columns. This kind of clustering is called <it>biclustering</it>. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed.</p> <p>Methods</p> <p>We introduce <it>BiMine</it>, a new enumeration algorithm for biclustering of DNA microarray data. The proposed algorithm is based on three original features. First, <it>BiMine </it>relies on a new evaluation function called <it>Average Spearman's rho </it>(ASR). Second, <it>BiMine </it>uses a new tree structure, called <it>Bicluster Enumeration Tree </it>(BET), to represent the different biclusters discovered during the enumeration process. Third, to avoid the combinatorial explosion of the search tree, <it>BiMine </it>introduces a parametric rule that allows the enumeration process to cut tree branches that cannot lead to good biclusters.</p> <p>Results</p> <p>The performance of the proposed algorithm is assessed using both synthetic and real DNA microarray data. The experimental results show that <it>BiMine </it>competes well with several other biclustering methods. Moreover, we test the biological significance using a gene annotation web-tool to show that our proposed method is able to produce biologically relevant biclusters. The software is available upon request from the authors to academic users.</p

The Susceptibility of Trypanosomatid Pathogens to PI3/mTOR Kinase Inhibitors Affords a New Opportunity for Drug Repurposing

In our study we describe the potency of established phosphoinositide-3-kinase (PI3K) and mammalian Target of Rapamycin (mTOR) kinase inhibitors against three trypanosomatid parasites: Trypanosoma brucei, T. cruzi, and Leishmania sp., which are the causative agents for African sleeping sickness, Chagas disease, and leishmaniases, respectively. We noted that these parasites and humans express similar kinase enzymes. Since these similar human targets have been pursued by the drug industry for many years in the discovery of cellular growth and proliferation inhibitors, compounds developed as human anti-cancer agents should also have effect on inhibiting growth and proliferation of the parasites. With that in mind, we selected eight established PI3K and mTOR inhibitors for profiling against these pathogens. Among these inhibitors is an advanced clinical candidate against cancer, NVP-BEZ235, which we demonstrate to be a highly potent trypanocide in parasite cultures, and in a mouse model of T. brucei infection. Additionally, we describe observations of these inhibitors' effects on parasite growth and other cellular characteristics