Design of novel compounds with the potential of dual PPARγ/α modulation for the management of metabolic syndrome

This study sought to identify a single molecule capable of managing all three manifestations of metabolic syndrome–hyperglycaemia, dyslipidaemia and hypertension. Two Protein Data Bank (PDB) depositions were selected and used to establish the baseline affinity that any designed molecule in this study should ideally exceed in order to be considered for further optimisation. These were PDB depositions 3VN2 and 2P54 describing the bound co-ordinates of the Peroxisome Proliferator Activated Receptor (PPAR) partial agonist and Angiotensin II Receptor (Ang(II)R) blocker telmisartan and of the experimental PPAR fibrate agonist GW590735 bound to their respective cognate receptors. These small molecules were extracted from their cognate receptors, docked into their non-cognate counterparts, conformational analysis performed, and the optimal conformers were selected as template scaffolds in two parallel processes. The first was a fragment based de novo approach. Here, molecular moieties from the optimal telmisartan and GW590735 scaffolds modelled in their non-cognate targets and considered critical to binding were identified and modelled, in order to produce seed structures capable of sustaining molecular growth at user-directed sites designated as H.spc atoms subsequent to their being docked within the non-cognate Ligand Binding Pockets (LBPs). The second approach was a Virtual Screening (VS) exercise. Here, the optimal telmisartan and GW590735 conformers were submitted as query molecules to VS databases both individually and in the form of a consensus pharmacophore. This VS exercise identified structurally diverse molecules which were electronically and spatially similar to the queries and which were capable of modulating the target receptors. The molecular cohorts identified through both VS and the de novo approaches were filtered for Lipinski Rule compliance. The molecules that survived filtering were then re-docked into the non-cognate PPAR and/or _LBPs, conformational analysis re-performed and the affinity of the optimal conformer measured for its cognate receptor quantified. Comparison was made to the baseline and non-cognate receptor affinities previously established, and the molecules exhibiting dual affinities exceeding baseline values were selected for further optimisation. The use of the “tried and tested” Ang(II)R blocker and fibrate scaffolds as templates predisposes to the identification of novel structures devoid of unacceptable toxicity.peer-reviewe

Bridging the Gap Between Traditional Metadata and the Requirements of an Academic SDI for Interdisciplinary Research

Metadata has long been understood as a fundamental component of any Spatial Data Infrastructure, providing information relating to discovery, evaluation and use of datasets and describing their quality. Having good metadata about a dataset is fundamental to using it correctly and to understanding the implications of issues such as missing data or incorrect attribution on the results obtained for any analysis carried out. Traditionally, spatial data was created by expert users (e.g. national mapping agencies), who created metadata for the data. Increasingly, however, data used in spatial analysis comes from multiple sources and could be captured or used by nonexpert users – for example academic researchers ‐ many of whom are from non‐GIS disciplinary backgrounds, not familiar with metadata and perhaps working in geographically dispersed teams. This paper examines the applicability of metadata in this academic context, using a multi‐national coastal/environmental project as a case study. The work to date highlights a number of suggestions for good practice, issues and research questions relevant to Academic SDI, particularly given the increased levels of research data sharing and reuse required by UK and EU funders

Using Free and Open Source GIS to Automatically Create Standards-Based Spatial Metadata in Academia - First Investigations

The importance of understanding the quality of data used in any GIS operation has increased significantly as a result of the advent of Free and Open Source (FOSS) tools and Open Data, which in turn have encouraged non-specialists to make use of GIS. Metadata (data about data) traditionally provides a description of this quality information and permits data curation, but it is frequently deemed as complex to create and maintain. Additionally, it is generally stored separately from the data, leading to issues where updates to the data are not reflected in the metadata and to users not being aware that metadata exists. This paper describes an approach to address these issues in an academic context - tightly coupling data and metadata and automating elements of standards-based metadata creation and automating keyword generation and language detection. We describe research into the potential of the FOSS packages Quantum GIS and PostGIS to support this form of metadata generation and maintenance

Integrating expertises and ambitions for data-driven digital building permits - the EUNET4DBP

The digitalization of the process for building permit (involving the use of 3D information systems) is seen as a priority in a wide part of the world. Since it is a very multidisciplinary use case, involving a variety of stakeholders tackling complex issues and topics, some of them joined their efforts and skills in the European Network for Digital Building Permit. The initial activity of the network, after a review of on-going experiences, was a workshop to share knowledge about the topics involved and to identify the main ambitions of the network with respect to three pillars (i.e. Process - Rules and Requirements - Technology) and the related requirements. It was achieved through a collective brainstorming activity guided by digital tools, whose results were further analysed in a post-processing phase. Such results are presented in this paper and will be the base for planning the future network activity. © Authors 2020

ŽELJKO HOLJEVAC GOSPIĆ U VOJNOJ KRAJINI

A range of novel heterocyclic cations have been synthesized by the Rh­(III)-catalyzed oxidative C–N and C–C coupling of 1-phenylpyrazole, 2-phenylpyridine, and 2-vinylpyridine with alkynes (4-octyne and diphenylacetylene). The reactions proceed via initial C–H activation, alkyne insertion, and reductive coupling, and all three of these steps are sensitive to the substrates involved and the reaction conditions. Density functional theory (DFT) calculations show that C–H activation can proceed via a heteroatom-directed process that involves displacement of acetate by the neutral substrate to form charged intermediates. This step (which leads to cationic C–N coupled products) is therefore favored by more polar solvents. An alternative non-directed C–H activation is also possible that does not involve acetate displacement and so becomes favored in low polarity solvents, leading to C–C coupled products. Alkyne insertion is generally more favorable for diphenylacetylene over 4-octyne, but the reverse is true of the reductive coupling step. The diphenylacetylene moiety can also stabilize unsaturated seven-membered rhodacycle intermediates through extra interaction with one of the Ph substituents. With 1-phenylpyrazole this effect is sufficient to suppress the final C–N reductive coupling. A comparison of a series of seven-membered rhodacycles indicates the barrier to coupling is highly sensitive to the two groups involved and follows the trend C–N⁺ > C–N > C–C (i.e., involving the formation of cationic C–N, neutral C–N, and neutral C–C coupled products, respectively)

Spectrum, risk factors and outcomes of neurological and psychiatric complications of COVID-19: a UK-wide cross-sectional surveillance study.

SARS-CoV-2 is associated with new-onset neurological and psychiatric conditions. Detailed clinical data, including factors associated with recovery, are lacking, hampering prediction modelling and targeted therapeutic interventions. In a UK-wide cross-sectional surveillance study of adult hospitalized patients during the first COVID-19 wave, with multi-professional input from general and sub-specialty neurologists, psychiatrists, stroke physicians, and intensivists, we captured detailed data on demographics, risk factors, pre-COVID-19 Rockwood frailty score, comorbidities, neurological presentation and outcome. A priori clinical case definitions were used, with cross-specialty independent adjudication for discrepant cases. Multivariable logistic regression was performed using demographic and clinical variables, to determine the factors associated with outcome. A total of 267 cases were included. Cerebrovascular events were most frequently reported (131, 49%), followed by other central disorders (95, 36%) including delirium (28, 11%), central inflammatory (25, 9%), psychiatric (25, 9%), and other encephalopathies (17, 7%), including a severe encephalopathy (n = 13) not meeting delirium criteria; and peripheral nerve disorders (41, 15%). Those with the severe encephalopathy, in comparison to delirium, were younger, had higher rates of admission to intensive care and a longer duration of ventilation. Compared to normative data during the equivalent time period prior to the pandemic, cases of stroke in association with COVID-19 were younger and had a greater number of conventional, modifiable cerebrovascular risk factors. Twenty-seven per cent of strokes occurred in patients 60 years old, the younger stroke patients presented with delayed onset from respiratory symptoms, higher rates of multi-vessel occlusion (31%) and systemic thrombotic events. Clinical outcomes varied between disease groups, with cerebrovascular disease conferring the worst prognosis, but this effect was less marked than the pre-morbid factors of older age and a higher pre-COVID-19 frailty score, and a high admission white cell count, which were independently associated with a poor outcome. In summary, this study describes the spectrum of neurological and psychiatric conditions associated with COVID-19. In addition, we identify a severe COVID-19 encephalopathy atypical for delirium, and a phenotype of COVID-19 associated stroke in younger adults with a tendency for multiple infarcts and systemic thromboses. These clinical data will be useful to inform mechanistic studies and stratification of patients in clinical trials

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study

Objective To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. Patients and Methods This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. Results Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3–34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1–30.2), UTUC (n = 128) 1.14% (95% CI 0.77–1.52), renal cancer (n = 107) 1.05% (95% CI 0.80–1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32–2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03–1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90–4.15; P < 0.001), male sex 1.30 (95% CI 1.14–1.50; P < 0.001), and smoking 2.70 (95% CI 2.30–3.18; P < 0.001). Conclusions A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

GeoBIM for built environment condition assessment supporting asset management decision making

The digital transformation in management of the built environment is more and more evident. While the benefits of location data, from Building Information Modelling or Geographical Information Systems, have been explored separately, their combination - GeoBIM - in asset management has never been explored. Data collection for condition assessment is challenging due to quantity, types, frequency and quality of data. We first describe the opportunities and challenges of GeoBIM for condition assessment. The theoretical approach is then validated developing an integrated GeoBIM model of the digital built environment, for a neighbourhood in Milan, Italy. Data are collected, linked, processed and analysed, through multiple software platforms, providing relevant information for asset management decision making. Good results are achieved in rapid massive data collection, improved visualisation, and analysis. While further testing and development is required, the case study outcomes demonstrated the innovation and the mid-term service-oriented potential of the proposed approach

Exploring CityEngine as a Visualisation Tool for 3D Cadastre

3D visualisation is a graphical way to identify and spatially communicate the complexity of a large number of real life situations of overlapping and encroachments in 2D or 3D land and property interests (e.g., buildings with complex architecture, infrastructures above or below Earth surface, natural resources and corresponding rights). Currently, several 3D visualisation applications and cadastral prototypes have been developed around the world. However, they still require maturation and validation by the users before being able to be used in real life situations. Thus, research on 3D cadastral visualisation needs more investigation. The 3D modelling of urban environments utilizes 3D visualisation systems. If these systems can somehow be reutilized in the 3D cadastre context, associate costs might be lower by building a system out of scratch. One of those systems is the ESRI CityEngine. This work proposes the evaluation of CityEngine’s suitability as a 3D cadastral visualisation tool, since it was not developed specifically for that purpose. This paper focuses primarily on 3D visualisation, not on data management or data delivery. The 3D visualisation requirements against which CityEngine was evaluated are classified into three main categories: cadastral requirements, visualisation requirements and non-functional requirements. The evaluation is made through a case study corresponding to a real situation in Portugal previously identified. Results obtained are promising, however it is necessary to carefully study other complex cases. However, the learning curve is steep and the CityEngine will not be the best option for all types of users