Cyclodextrins for oral liquid paediatric drug delivery: Application to corticosteroids

In the present research, the ability of cyclodextrins (CDs) to solubilise and taste mask poorly soluble bitter drugs was assessed by various analytical techniques, including a novel in vitro taste analyser, to propose CDs as excipients for oral liquid paediatric formulations. Corticosteroids were selected as model drugs because of their relevance in paediatrics, whilst model bitter drug quinine was also selected to provide comparative data. Aside from various inclusion complex characteristics, such as stability constants and complexation efficiencies, phase solubility studies determined that: the CDs formed soluble 1:1 inclusion complexes with the corticosteroids studied, the CD derivatives were capable of providing adequate paediatric dose volumes, simulated media in vivo and pH did not to have a major influence on inclusion complexation. The presence of preservatives, however, reduced CD solubility efficiency, whilst reducing the preservative efficiency. ITC studies determined that inclusion complexation with corticosteroids was a spontaneous process and various interactions involved with complexation were proposed. 1H NMR spectroscopy studies indicated that CDs formed inclusion complexes with the corticosteroids, whereby the drug molecules entered the CD cavities via the wider cavity opening. Human taste panel studies demonstrated that CDs were able to taste mask corticosteroids, often more efficiently than traditional taste masking agents, and with 10 times more drug being incorporated in the formulation. Excess CD was also observed to be more efficient at taste masking corticosteroids than molar equivalent concentrations. From these taste panel results, a mechanism of CD taste masking was proposed. Preliminary electronic tongue analysis was found to be able to select concentrations of various taste masking agents for subsequent taste masking assessment. Nevertheless, little correlation was found between the assessment of the electronic tongue and the human taste panel, thus limiting the legitimacy of the instrument for this application. This research has shown that CDs could be utilised in oral liquid paediatric formulations to provide dose uniformity, appropriate volume, and acceptable palatability for poorly soluble bitter drugs. Further work is required to examine the acceptability & bioavailability of these formulations in paediatric patients

Ganglion Blocking Agents

Abstract Not Provided

How do Board Characteristics Influence Business Performance? Evidence from Non-life Insurance Firms in Zimbabwe.

Objective: The purpose of this study was to contribute to the corporate governance literature by establishing the relationship between board characteristics and corporate performance within the non-life insurance firms in Zimbabwe. The study sought to provide some insights on corporate governance since the phenomenon is relatively an emerging discipline in Zimbabwe. Prior Work: The paper sought to complement other corporate governance studies that were conducted in other environments by producing evidence on the phenomenon from a developing country context. Approach: A quantitative research approach was adopted and respondents were selected through a stratified random sampling. Results: The results of the study confirm that board characteristics (board composition, diversity, and size) exhibit a statistically significant positive predictive relationship with the performance of non-life insurance firms measured by gross premium written and customer retention. However, CEO/Chairman duality showed a negative relationship with business performance. Implications: Non-life insurance companies need to be cognizant of board characteristics in order to improve their performance. Moreover , the findings in this research has practical relevance for the selection process of directors as it highlights the importance of having a sizeable number of board members as well as an appropriate mix of competences and qualifications on the board. Value: Although corporate governance is has been extensively researched, there is limited study in this area from a developing country like Zimbabwe with relatively less developed capital markets. It would be wrong to assume that the findings found in other countries can apply here because the conditions are different.   JEL: O16 &nbsp

Hear Me Out: A Study on the Use of the Voice Modality for Crowdsourced Relevance Assessments

The creation of relevance assessments by human assessors (often nowadays crowdworkers) is a vital step when building IR test collections. Prior works have investigated assessor quality & behaviour, though into the impact of a document's presentation modality on assessor efficiency and effectiveness. Given the rise of voice-based interfaces, we investigate whether it is feasible for assessors to judge the relevance of text documents via a voice-based interface. We ran a user study (n = 49) on a crowdsourcing platform where participants judged the relevance of short and long documents sampled from the TREC Deep Learning corpus-presented to them either in the text or voice modality. We found that: (i) participants are equally accurate in their judgements across both the text and voice modality; (ii) with increased document length it takes participants significantly longer (for documents of length > 120 words it takes almost twice as much time) to make relevance judgements in the voice condition; and (iii) the ability of assessors to ignore stimuli that are not relevant (i.e., inhibition) impacts the assessment quality in the voice modality-assessors with higher inhibition are significantly more accurate than those with lower inhibition. Our results indicate that we can reliably leverage the voice modality as a means to effectively collect relevance labels from crowdworkers.Comment: Accepted at SIGIR 202

Short term impact of smoke-free legislation in England: retrospective analysis of hospital admissions for myocardial infarction

Objective To measure the short term impact on hospital admissions for myocardial infarction of the introduction of smoke-free legislation in England on 1 July 2007

Apolipoprotein E4 has extensive conformational heterogeneity in lipid-free and lipid-bound forms

The ε4-allele variant of apolipoprotein E (ApoE4) is the strongest genetic risk factor for Alzheimer\u27s disease, although it only differs from its neutral counterpart ApoE3 by a single amino acid substitution. While ApoE4 influences the formation of plaques and neurofibrillary tangles, the structural determinants of pathogenicity remain undetermined due to limited structural information. Previous studies have led to conflicting models of the C-terminal region positioning with respect to the N-terminal domain across isoforms largely because the data are potentially confounded by the presence of heterogeneous oligomers. Here, we apply a combination of single-molecule spectroscopy and molecular dynamics simulations to construct an atomically detailed model of monomeric ApoE4 and probe the effect of lipid association. Importantly, our approach overcomes previous limitations by allowing us to work at picomolar concentrations where only the monomer is present. Our data reveal that ApoE4 is far more disordered and extended than previously thought and retains significant conformational heterogeneity after binding lipids. Comparing the proximity of the N- and C-terminal domains across the three major isoforms (ApoE4, ApoE3, and ApoE2) suggests that all maintain heterogeneous conformations in their monomeric form, with ApoE2 adopting a slightly more compact ensemble. Overall, these data provide a foundation for understanding how ApoE4 differs from nonpathogenic and protective variants of the protein

Chapter 21 Artificial intelligence and data analytics for geosciences and remote sensing theory and application

To address the limitation of conventional statistics in dealing with hyperspectral data of satellite and airborne images, two contextual analyses are introduced in this chapter. The first case study presents the development of an artificial intelligence (AI) and data analytics algorithm capable of classifying hyperspectral data to support remote sensing and geographic information systems researchers in understanding and predicting changes in natural earth processes. The classification algorithm is based on a fuzzy approach combining a decision tree classifier with a fuzzy multiple-criteria decision analysis classifier. The second case study presents the development of an AI tool that extracts features from the hyperspectral data to transform a two-dimensional (2D) satellite and airborne picture to a pseudo-3D picture to improve complexity and produce multidirectional sun-shaded pictures and their edges. Such 3D images are useful in supporting the discovery of prospective ground for mineral exploration, extraction from the earth of precious minerals or other geological materials, usually from deposits of ore, veins, lodes, seams, reefs, or placer deposits, and overall to improve the efficiency and effectiveness of mineral exploration