Machine Intelligence for Advanced Medical Data Analysis: Manifold Learning Approach

In the current work, linear and non-linear manifold learning techniques, specifically Principle Component Analysis (PCA) and Laplacian Eigenmaps, are studied in detail. Their applications in medical image and shape analysis are investigated. In the first contribution, a manifold learning-based multi-modal image registration technique is developed, which results in a unified intensity system through intensity transformation between the reference and sensed images. The transformation eliminates intensity variations in multi-modal medical scans and hence facilitates employing well-studied mono-modal registration techniques. The method can be used for registering multi-modal images with full and partial data. Next, a manifold learning-based scale invariant global shape descriptor is introduced. The proposed descriptor benefits from the capability of Laplacian Eigenmap in dealing with high dimensional data by introducing an exponential weighting scheme. It eliminates the limitations tied to the well-known cotangent weighting scheme, namely dependency on triangular mesh representation and high intra-class quality of 3D models. In the end, a novel descriptive model for diagnostic classification of pulmonary nodules is presented. The descriptive model benefits from structural differences between benign and malignant nodules for automatic and accurate prediction of a candidate nodule. It extracts concise and discriminative features automatically from the 3D surface structure of a nodule using spectral features studied in the previous work combined with a point cloud-based deep learning network. Extensive experiments have been conducted and have shown that the proposed algorithms based on manifold learning outperform several state-of-the-art methods. Advanced computational techniques with a combination of manifold learning and deep networks can play a vital role in effective healthcare delivery by providing a framework for several fundamental tasks in image and shape processing, namely, registration, classification, and detection of features of interest

Mutations in NKX6-2 Cause Progressive Spastic Ataxia and Hypomyelination

Progressive limb spasticity and cerebellar ataxia are frequently found together in clinical practice and form a heterogeneous group of degenerative disorders that are classified either as pure spastic ataxia or as complex spastic ataxia with additional neurological signs. Inheritance is either autosomal dominant or autosomal recessive. Hypomyelinating features on MRI are sometimes seen with spastic ataxia, but this is usually mild in adults and severe and life limiting in children. We report seven individuals with an early-onset spastic-ataxia phenotype. The individuals come from three families of different ethnic backgrounds. Affected members of two families had childhood onset disease with very slow progression. They are still alive in their 30s and 40s and show predominant ataxia and cerebellar atrophy features on imaging. Affected members of the third family had a similar but earlier-onset presentation associated with brain hypomyelination. Using a combination of homozygozity mapping and exome sequencing, we mapped this phenotype to deleterious nonsense or homeobox domain missense mutations in NKX6-2. NKX6-2 encodes a transcriptional repressor with early high general and late focused CNS expression. Deficiency of its mouse ortholog results in widespread hypomyelination in the brain and optic nerve, as well as in poor motor coordination in a pattern consistent with the observed human phenotype. In-silico analysis of human brain expression and network data provides evidence that NKX6-2 is involved in oligodendrocyte maturation and might act within the same pathways of genes already associated with central hypomyelination. Our results support a non-redundant developmental role of NKX6-2 in humans and imply that NKX6-2 mutations should be considered in the differential diagnosis of spastic ataxia and hypomyelination

Criteria for Establishing Priorities in Sidewalk Maintenance When Using Multi-Criteria Analysis in Order to Achieve Inclusive Mobility

To create an inclusive city, it is essential to have accessible pedestrian infrastructure. The accessibility of pedestrian infrastructure is ensured through the proper maintenance of sidewalks. When resources are limited, it is necessary to prioritize sidewalks by identifying those in the most critical condition, and this is often achieved through multi-criteria analyses. This paper proposed an analysis of the criteria to be considered, which include not only pavement distresses but also the importance of the sidewalk in connecting various parts of the city and ensuring accessibility to significant places for all, including vulnerable users. Methodologies for evaluating a sidewalk in relation to these criteria were proposed and an application of these methods to a simple case study in Genoa was presented. In this context, the evaluation of the criteria weights was performed using subjective and objective methods. The weights calculated with the two methods generated the same priorities. All the experts interviewed agreed with the proposed set of criteria and two experts suggested considering a new criterion relating to the level of danger of the context in which a pavement is located

Intelligent negotiation model for ubiquitous group decision scenarios

Supporting group decision-making in ubiquitous contexts is a complex task that must deal with a large amount of factors to succeed. Here we propose an approach for an intelligent negotiation model to support the group decision-making process specially designed for ubiquitous contexts. Our approach can be used by researchers that intend to include arguments, complex algorithms and agents' modelling in a negotiation model. It uses a social networking logic due to the type of communication employed by the agents and it intends to support the ubiquitous group decision-making process in a similar way to the real process, which simultaneously preserves the amount and quality of intelligence generated in face-to-face meetings. We propose a new look into this problematic by considering and defining strategies to deal with important points such as the type of attributes in the multicriteria problems, agents' reasoning and intelligent dialogues.This work has been supported by COMPETE Programme (operational programme for competitiveness) within project POCI-01-0145-FEDER-007043, by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within the Projects UID/CEC/00319/2013, UID/EEA/00760/2013, and the João Carneiro PhD grant with the reference SFRH/BD/89697/2012 and by Project MANTIS - Cyber Physical System Based Proactive Collaborative Maintenance (ECSEL JU Grant nr. 662189).info:eu-repo/semantics/publishedVersio

DprE2 is a molecular target of the anti-tubercular nitroimidazole compounds pretomanid and delamanid

Abstract Mycobacterium tuberculosis is one of the global leading causes of death due to a single infectious agent. Pretomanid and delamanid are new antitubercular agents that have progressed through the drug discovery pipeline. These compounds are bicyclic nitroimidazoles that act as pro-drugs, requiring activation by a mycobacterial enzyme; however, the precise mechanisms of action of the active metabolite(s) are unclear. Here, we identify a molecular target of activated pretomanid and delamanid: the DprE2 subunit of decaprenylphosphoribose-2’-epimerase, an enzyme required for the synthesis of cell wall arabinogalactan. We also provide evidence for an NAD-adduct as the active metabolite of pretomanid. Our results highlight DprE2 as a potential antimycobacterial target and provide a foundation for future exploration into the active metabolites and clinical development of pretomanid and delamanid

Effects of nanoencapsulated formulation of Cuminum cyminum essential oil on Panonychus citri (Acari: Tetranychidae)

Citrus red mite, Panonychus citri McGregor is one of the most important pests of citrus orchards in the world. Due to excessive use of chemical pesticides and development of resistance plus their increasing environmental hazards, the use of essential oils has been highly studied. But the low solubility of essential oils in water, oxidation, in addition to their instability in presence of light, humidity and high temperature has diminished their application. Formulation technology is one of the main strategies that can modify the physical properties and the viability of the essential oils in agricultural pest management programs. In this research, the essential oil of Cuminum cyminum L. was encapsulated by in situ polymerization of oil/water emulsion in nano scale and then the effects of nanoencapsulated essential oil (NEO) were analyzed against P. citri. The results showed that LC50 of NEO's contact toxicity was 743.17 ppm over 24 hours. NEO also affected mortality and decreased oviposition rate in P. citri. NEO had deterrence capacity at 300, 500 and 700 ppm. Moreover, NOE had oviposition deterrence, lowering the number of eggs per female compared to the control. Our finding suggests that high-tech formulations including nanoencapsulation technology can be used as botanical pesticides and as alternatives to chemical pesticides

Facile Stereoselective Reduction of Prochiral Ketones by using an F ₄₂₀-dependent alcohol dehydrogenase

Effective procedures for the synthesis of optically pure alcohols are highly valuable. A commonly employed method involves the biocatalytic reduction of prochiral ketones. This is typically achieved by using nicotinamide cofactor-dependent reductases. In this work, we demonstrate that a rather unexplored class of enzymes can also be used for this. We used an F420-dependent alcohol dehydrogenase (ADF) from Methanoculleus thermophilicus that was found to reduce various ketones to enantiopure alcohols. The respective (S) alcohols were obtained in excellent enantiopurity (>99 % ee). Furthermore, we discovered that the deazaflavoenzyme can be used as a self-sufficient system by merely using a sacrificial cosubstrate (isopropanol) and a catalytic amount of cofactor F420 or the unnatural cofactor FOP to achieve full conversion. This study reveals that deazaflavoenzymes complement the biocatalytic toolbox for enantioselective ketone reductions

Rebalancing static bike-sharing systems: a two-period two-commodity multi-depot mathematical model

In this paper, an Integer Linear Programming (ILP) has been developed for rebalancing the stations of a Periodic Bike Relocation Problem (PBRP) in multiple periods. The objective function of the mathematical model is reducing costs of implementing trucks, transportation between stations and holding bikes on trucks during rebalancing. The variables we are following them in this model are conducting the optimal route in several periods, using the most appropriate trucks for these routes, and determining the best program for loading/unloading bikes for stations. The distinguishing features of the proposed model are considering several bike types, several exclusive trucks and several time periods. Finally, a numerical example confirms the applicability of the proposed model