Advanced structural characterisation of pharmaceuticals using nano-thermal analysis (nano-TA)

The production of drug delivery systems fabricated at the nano scale comes with the challenges of identifying reliable characterisation tools, especially for solid dosage forms. A full understanding of physicochemical properties of solid-state systems at a high spatial resolution is essential to monitor their manufacturability, processability, performance (dissolution) and stability. Nano-thermal analysis (nano-TA), a hybrid of atomic force microscopy (AFM) and thermal analysis, has emerged as a solution to address the need for complete characterisation of samples with surface heterogeneity. Nano-TA provides not only physical information using conventional AFM but also the thermal behaviour of these systems as an additional chemical dimension. In this review, the principles and techniques of nano-TA are discussed with emphasis on recent pharmaceutical applications. Building on nano-TA, the combination of this approach with infrared spectroscopic analysis is briefly introduced. The challenges and considerations for future development of nano-TA characterisation are also outlined

The application of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the stratum corneum

Drug permeation through the intercellular lipids, which pack around and between corneocytes, may be enhanced by increasing the thermodynamic activity of the active in a formulation. However, this may also result in unwanted drug crystallisation on and in the skin. In this work, we explore the combination of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the skin. Ex vivo permeation studies of saturated solutions of diclofenac sodium (DF Na) in two vehicles, propylene glycol (PG) and dimethyl sulphoxide (DMSO), were carried out in porcine ear skin. Tape stripping and ATR-FTIR spectroscopy were conducted simultaneously to collect spectral data as a function of skin depth. Multivariate data analysis was applied to visualise and categorise the spectral data in the region of interest (1700-1500cm(-1)) containing the carboxylate (COO(-)) asymmetric stretching vibrations of DF Na. Spectral data showed the redshifts of the COO(-) asymmetric stretching vibrations for DF Na in the solution compared with solid drug. Similar shifts were evident following application of saturated solutions of DF Na to porcine skin samples. Multivariate data analysis categorised the spectral data based on the spectral differences and drug crystallisation was found to be confined to the upper layers of the skin. This proof-of-concept study highlights the utility of ATR-FTIR spectroscopy in combination with multivariate data analysis as a simple and rapid approach in the investigation of drug deposition in the skin. The approach described here will be extended to the study of other actives for topical application to the skin

Sources of variability in the prospective relation of language to social, emotional, and behavior problem symptoms: Implications for developmental language disorder

Children with developmental language disorder (DLD) are at risk for social, emotional, and behavioral (SEB) maladjustment throughout development, though it is unclear if poor language proficiency per se can account for this risk as associations between language and SEB appear more variable among typical-language children. This study investigated whether the relationship between language and SEB problems is stronger at very low levels of language and considered confounders including socioeconomic status, sex, and nonverbal intelligence. These were examined using a population-based survey design, including children with a wide range of language and cognitive profiles, and assessed using the Strengths and Difficulties Questionnaire and six standardized language measures (n = 363, weighted n = 6,451). Structural equation models adjusted for prior levels of SEB revealed that the relationship of language at age 5–6 years to SEB at 7–9 years was nonlinear. Language more strongly predicted all clusters of SEB at disordered language levels relative to typical language levels, with standardized betas of −.25 versus .03 for behavioral, −.31 versus −.04 for peer, and .27 versus .03 for prosocial problems. Wald tests between these pairs of betas yielded p values from .049 to .014. Sex moderated the nonlinear association between language and emotional symptoms. These findings indicate a clinical need to support language development in order to mitigate against problems of SEB and to carefully monitor the mental health needs of children with DLD, particularly in the context of multiple, and potentially sex-specific, risks

Spatial resolution of drug crystallisation in the skin by X-ray micro-computed tomography

Drug crystallisation in the skin is recognised as a significant problem in topical and transdermal drug delivery. Our recent investigations provided new evidence of drug crystallisation in the skin, however, confirming the precise location of crystals remains challenging. Of note, most approaches used have required disruption of the membrane by tape stripping, with crystal detection limited to the superficial skin layers. Hence, a non-destructive method for complete spatial resolution of crystallised drug in skin is still lacking. In this communication, we report the application of X-ray micro-computed tomography (microCT) to examine drug crystallisation in mammalian skin ex vivo. Permeation studies of a saturated solution of diclofenac sodium were conducted in porcine skin; subsequently, tissue samples were scanned using microCT to generate 2D and 3D maps. A layer of drug crystals was observed on the skin surface; microCT maps also confirmed the distribution of drug crystals up to a skin depth of 0.2 – 0.3 mm. MicroCT also allowed the identification of drug crystallisation as a distinct and confirmed event in the skin and as an extension from drug crystals formed on the skin. These preliminary results confirm the potential of microCT to study this important phenomenon in topical and transdermal drug delivery

Nano-thermal imaging of the stratum corneum and its potential use for understanding of the mechanism of skin penetration enhancer

Nano-thermal analysis (nano-TA) is a localised thermal technique which maps a surface in terms of thermal transitions by combining atomic force microscopy with the use of thermal probes, allowing a spatial resolution of sub–100 nm. In this communication, we describe the application of a localised nano-TA approach, transition temperature microscopy (TTM), to investigate the thermotropic properties of porcine stratum corneum (PSC) as a function of depth and the influence of penetration enhancer on the nano-thermal properties of PSC. The investigations were conducted on PSC removed using tape strips. The transition temperature of PSC recorded at ∼220 °C was ascribed to protein denaturation/degradation. A decrease in the transition temperature was observed with an increase of skin depth. ‘Transition depression’ was observed when PSC was treated with propylene glycol, suggesting its water extraction effect on SC protein and a drop in the biomechanical properties of the SC. TTM has the potential to be extended to on in situ investigations of various penetration enhancers

The TURis System for Transurethral Resection of the Prostate: A NICE Medical Technology Guidance

The transurethral resection in saline (TURis) system was notified by the company Olympus Medical to the National Institute of Health and Care Excellence’s (NICE’s) Medical Technologies Evaluation Programme. Following selection for medical technologies guidance, the company developed a submission of clinical and economic evidence for evaluation. TURis is a bipolar surgical system for treating men with lower urinary tract symptoms due to benign prostatic enlargement. The comparator is any monopolar transurethral resection of the prostate (mTURP) system. Cedar, a collaboration between Cardiff and Vale University Health Board, Cardiff University and Swansea University in the UK, acted as an External Assessment Centre (EAC) for NICE to independently critique the company’s submission of evidence. Eight randomised trials provided evidence for TURis, demonstrating efficacy equivalent to that of mTURP for improvement of symptoms. The company presented meta-analyses of key outcome measures, and the EAC made methodological modifications in response to the heterogeneity of the trial data. The EAC analysis found that TURis substantially reduced the relative risks of transurethral resection syndrome (relative risk 0.18 [95 % confidence interval 0.05–0.62]) and blood transfusion (relative risk 0.35 [95 % confidence interval 0.19–0.65]). The company provided a de novo economic model comparing TURis with mTURP. The EAC critiqued the model methodology and made modifications. This found TURis to be cost saving at £70.55 per case for existing Olympus customers and cost incurring at £19.80 per case for non-Olympus customers. When an additional scenario based on the only available data on readmission (due to any cause) from a single trial was modelled, the estimated cost saving per case was £375.02 for existing users of Olympus electrosurgery equipment and £284.66 per case when new Olympus equipment would need to be purchased. Meta-analysis of eight randomised trials showed that TURis is associated with a statistically significantly reduced risk of transurethral resection syndrome and a reduced need for blood transfusion—two factors that may drive cost saving for the National Health Service. The clinical data are equivocal as to whether TURis shortens the hospital stay. Limited data from a single study suggest that TURis may reduce the rate of readmission after surgery. The NICE guidance supports adoption of the TURis technology for performing transurethral resection of the prostate in men with lower urinary tract symptoms due to benign prostatic enlargemen

Teaching Engineering Ethics using BLOCKS Game

The aim of this study was to investigate the use of a newly developed design game called BLOCKS to stimulate awareness of ethical responsibilities amongst engineering students. The design game was played by seventeen teams of chemical engineering students, with each team having to arrange pieces of colored paper to produce two letters each. Before the end of the game, additional constraints were introduced to the teams such that they faced similar ambiguity in the technical facts that the engineers involved in the Challenger disaster had faced prior to the space shuttle launch. At this stage, the teams had to decide whether to continue with their original design or to develop alternative solutions. After the teams had made their decisions, a video of the Challenger explosion was shown followed by a post-game discussion. The students’ opinion on five Statements on ethics was tracked via a Five-Item Likert survey which was administered three times, before and after the ethical scenario was introduced, and after the video and post-game discussion. The results from this study indicated that the combination of the game and the real-life incident from the video had generally strengthened the students’ opinions of the Statements

Symbols in engineering drawings (SiED): an imbalanced dataset benchmarked by convolutional neural networks.

Engineering drawings are common across different domains such as Oil & Gas, construction, mechanical and other domains. Automatic processing and analysis of these drawings is a challenging task. This is partly due to the complexity of these documents and also due to the lack of dataset availability in the public domain that can help push the research in this area. In this paper, we present a multiclass imbalanced dataset for the research community made of 2432 instances of engineering symbols. These symbols were extracted from a collection of complex engineering drawings known as Piping and Instrumentation Diagram (P&ID). By providing such dataset to the research community, we anticipate that this will help attract more attention to an important, yet overlooked industrial problem, and will also advance the research in such important and timely topics. We discuss the datasets characteristics in details, and we also show how Convolutional Neural Networks (CNNs) perform on such extremely imbalanced datasets. Finally, conclusions and future directions are discussed

The use of Bayesian latent class cluster models to classify patterns of cognitive performance in healthy ageing

The main focus of this study is to illustrate the applicability of latent class analysis in the assessment of cognitive performance profiles during ageing. Principal component analysis (PCA) was used to detect main cognitive dimensions (based on the neurocognitive test variables) and Bayesian latent class analysis (LCA) models (without constraints) were used to explore patterns of cognitive performance among community-dwelling older individuals. Gender, age and number of school years were explored as variables. Three cognitive dimensions were identified: general cognition (MMSE), memory (MEM) and executive (EXEC) function. Based on these, three latent classes of cognitive performance profiles (LC1 to LC3) were identified among the older adults. These classes corresponded to stronger to weaker performance patterns (LC1>LC2>LC3) across all dimensions; each latent class denoted the same hierarchy in the proportion of males, age and number of school years. Bayesian LCA provided a powerful tool to explore cognitive typologies among healthy cognitive agers.The study is integrated in the "Maintaining health in old age through homeostasis (SWITCHBOX)" collaborative project funded by the European Commission FP7 initiative (grant HEALTH-F2-2010-259772). NS and JAP are main team members of the European consortium SWITCHBOX (http://www.switchbox-online.eu/). NCS is supported by a SwitchBox post-doctoral fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript