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Green Chemistry Methods for Analysing Microalgae Pigments
No full textThis chapter focuses on green analytical chemistry that aims at minimising resources and energy guided by ethical considerations and environmental sustainability. It based on four principles: (1) elimination or reduction of reagents and
solvents, (2) reduction of emissions, (3) elimination of toxic reagents, and (4) reduction of labour and energy. These principles underline a need to provide alternative
solutions to high-cost sophisticated equipment and promote a rapid shift to a low-cost
and readily available instrumentation and analytical solutions with appropriate levels
of accuracy, sensitivity, and selectivity. Microalgae is a rich source of bioactives and
presents a great challenge to analyse and isolate its content. Many technological advances are tailored to individual components generating unnecessary waste and unsustainable use of resources. In this context, this chapter focuses on most recent
published work on the sample preparation and extraction techniques enabling efficient release of value-added chemicals. A use of ‘greener’ solvents such as ionic liquids, super critical carbon dioxide is explored in attempt to compare them to
traditional solvents. Most literature concentrates on the cell wall disruption to facil itate the process of releasing target molecules to improve yield and purity. Thus,
chapter focuses on eco-friendly approaches and synergistic strategies of combined non-mechanical e.g., thermal, chemical, and enzymatic with mechanical e.g., ultrasonication, electric field, and microwaves treatments. Although life cycle analysis (LCA) is routinely used in many sectors as a measure of ‘sustainability’ it is rarely
employed for extractions of bioactives. This chapter also explores a ‘suitability’ of LCA approach in the context of microalgae
The secondary care (hospital) cost of treating and rehabilitating patients with head and neck cancer
Get PDFBackground
The cost of head and neck cancer treatment is of interest to clinicians and providers. The aim of this work was to estimate the costs of treating and rehabilitating patients following different head and neck cancer diagnoses.
Design
A single-centre retrospective cohort study using purposive sampling of patient records. Patient-level costing was performed using the hospital's Patient Level Information and Costing System (PLICS), capturing costs across surgical, radiotherapeutic, and oral rehabilitation pathways.
Results
Ten patients were included. Treatment costs ranged from £15,560 to £69,536. Advanced-stage cancers were costly, requiring multi-modality treatment and complex oral rehabilitation. Primary dental implant placement was more cost-effective than delayed placement.
Conclusion
There is substantial variability in the cost of curative treatment and oral rehabilitation for head and neck cancer. Stage at diagnosis and modality of rehabilitation significantly influence total cost. These findings support the economic rationale for early detection and standardised rehabilitation protocols
Health disparities in transitions between kidney replacement therapy modalities and mortality in England: a multistate model using UK Renal Registry data
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While ethnic and deprivation-related disparities in kidney replacement therapy (KRT) initiation are well established, their impact on transitions between treatment modalities and mortality over the course of kidney failure remains poorly understood. This study aimed to examine the association between ethnicity and area-level deprivation and the rates of transition between treatment modalities and death across the patient life course on KRT.
Methods and findings
We used a parametric multistate model to analyse UK Renal Registry data from 93,451 patients initiating KRT in England between 2005 and 2020 with a median follow-up of 1,497 days [IQR: 640−2,841] (4.1 years [IQR: 1.75,7.8]). We estimated transition-specific hazard rates and probabilities between peritoneal dialysis (PD), home haemodialysis (HHD), in-centre haemodialysis (ICHD), transplantation, and death using Weibull proportional hazard models. Ethnicity and area-level deprivation (measured by quintiles of the Index of Multiple Deprivation [IMD]) were included as covariates of primary interest, with models additionally adjusted for sex, age and diabetes mellitus as the primary kidney disease (PKD). Compared with White patients, Asian patients had lower transition rates from ICHD to PD (hazard ratio [HR]: 0.68, 95% confidence interval [CI] [0.51,0.91]), and from PD to ICHD (HR 0.85, 95% CI [0.78,0.92]), but a higher rate of returning to ICHD after transplantation (HR 1.12, 95% CI [1.01,1.24]). Black patients also had lower transition rates from ICHD to PD (HR 0.64, 95% CI [0.47,0.88]) and to HHD (HR 0.47, 95% CI [0.37,0.61]), but higher rates of transition from PD to ICHD (HR 1.16, 95% CI [1.01,1.33]) and from transplantation to ICHD (HR 1.73, 95% CI [1.44,2.08]). Patients living in the most deprived areas had lower transition rates from ICHD to PD (HR 0.63, 95% CI [0.56,0.70]), to HHD (HR 0.49, 95% CI [0.38,0.64]), and to transplantation (HR 0.57, 95% CI [0.52,0.64]), and higher rates from transplantation to ICHD (HR 1.63, 95% CI [1.43,1.85]) and to death (HR 1.53, 95% CI [1.33,1.76]), compared with those from the least deprived areas. A limitation of our study is that, apart from diabetes mellitus as the PKD, comorbidities were not included in the analysis due to incomplete reporting in the UK Renal Registry. This should be considered when interpreting the observed disparities, particularly those related to area-level deprivation.
Conclusions
These findings highlight persistent inequalities throughout the KRT pathway. The multistate modelling framework applied in this study offers a foundation for future research to design and evaluate interventions that improve equity and patient outcomes in kidney care
The relationship of osmolality and kidney outcomes in patients with autosomal dominant polycystic kidney disease
Get PDFBackground
Current treatment of autosomal dominant polycystic kidney disease (ADPKD) is mainly focused on inhibiting cystogenesis through arginine vasopressin suppression and there have been interests in achieving similar vasopressin suppression by reduction of osmolality with increased water intake. However, the causal relationship between serum osmolality and kidney outcome remained unclear in ADPKD patients. We aim to evaluate the relationship of serum osmolality and its effect on kidney outcome in ADPKD patients.
Methods
Three hundred and eleven tolvaptan treatment-naïve ADPKD patients were recruited prospectively from the CysticHK cohort, a territory-wide ADPKD registry across twelve tertiary hospitals in Hong Kong. Beside clinical data, serial measurement of serum and urinary osmolality were obtained every six months over five years. All participants were treated according to the standard of clinical care. The primary outcome was the 40% decline from baseline eGFR.
Results
Patients with a high serum osmolality have a worse kidney outcome, as shown by the Kaplan-Meier plots (log-rank p=<0.001) and the Cox regression model that showed a 5.91 times higher risk of reaching 40% eGFR decline compared to the top with bottom quartiles of osmolality (p=0.018). In contrast, there is an inverse relationship for urine osmolality. A ROC analysis to assess the predictive efficacy of osmolality for identifying those at high risk of kidney decline also showed a good performance for serum osmolality (AUC 0.81, 95%CI, 0.73-0.89; p<0.001). The urinary osmolality did not show a clinical meaningful predictive efficacy (AUC 0.35, 95%CI 0.28-0.43; p=0.003).
Conclusions
Serum osmolality may be a possible surrogate marker for the clinical monitoring of ADPKD patients, especially when access to copeptin level is limited; and high serum osmolality conveys possible detrimental effect on the kidney outcomes
Low-frequency resonators filled with granular material for modal response treatment
Get PDFResonators are commonly employed as passive dampers to suppress structural vibrations. This study proposes a novel resonator concept designed for low-frequency control of a host structure, incorporating a granular-filled cavity to enhance damping and enable tunability of the target modal response. The resonator can be manufactured using additive techniques, and its resonant behaviour is estimated empirically from its geometry and material properties. The effect of multiple resonators on the modal response of the main structure is shown numerically and experimentally offering wider attenuation frequency bandwidth where bending modes of the main structure are successfully controlled. Incorporating only 10% volume fraction of granular material in resonator that have a negligible effect on its overall mass yields an additional 45% damping improvement and expands the effective attenuation bands
Demand correlation and PV solar panel investment
Get PDFThe globe is entering an age of electricity, with renewable sources at the forefront of growth in investment in the transition. This study takes a novel step by theoretically and empirically contributing to our understanding of how investment in residential solar photovoltaics (PV) increases with demand correlation, and the extent to which this relationship is shaped by demand uncertainty. We bring together a unique dataset of relevant information about solar PV investment and electricity demand in GB between 2015 and 2020. This allows us to test our theoretical predictions and empirically show that (i) households invest more when demand correlation increases and that (ii) this relationship is amplified when demand is uncertain
Translating in vitro buccal permeation to in vivo and whole‑body exposure using in silico cell‑based and physiologically-based pharmacokinetic modelling
Get PDFThere is increasing interest in the delivery of chemicals to or through the oral buccal mucosa to avoid first-pass metabolism by the liver or the use of needles, which are associated with oral or parenteral administration. Moreover, buccal mucosa is several times more permeable than skin, making it an attractive route for controlled drug delivery via mucoadhesive films, tablets, and patches. Developing in silico models to predict rates of chemical permeation would greatly expediate experimental discovery to clinical use. However, predicting chemical permeation through the buccal mucosa is challenging due to limited availability of ex vivo human tissue for experimentation. Previously, we used tissue engineered buccal mucosa to parameterise an in silico model of buccal chemical permeation using partial differential equations, fitted to in vitro generated chemical permeation data of chemicals with known physiochemical properties. Here, we describe a new approach to predict in vivo permeation from in vitro data. The importance of the permeability barrier is included explicitly in the in silico models by parameterising from in vitro permeation experiments on buccal epithelium with fully formed or deficient permeability barriers. In vivo predictions are made by mapping mechanistic parameters, fitted to in vitro data, to in vivo cell geometry including cell layer thicknesses, cell-sizes and extracellular space. The predictions are tied to a physiologically-based pharmacokinetic model for whole-body chemical distribution that is validated against in vivo data. This combined in vitro-in silico approach has the potential to reduce animal experimentation and improve in vivo predictions for human buccal mucosa
Enhancing the Functionality of Soft Continuum Robots for Minimally Invasive and Endoluminal Interventions: A Review
No full textThe introduction and development of soft continuum robots for minimally invasive surgery and endoluminal intervention offers a promising option for navigating delicate, convoluted human anatomy across various procedures. However, successful translation of soft continuum robots from research prototypes through to clinically viable tools relies on overcoming the challenge of functionalization for targeted diagnostic and therapeutic intervention. Functionalization demands specialized design and fabrication strategies to ensure practical integration of operational components, such as stimuli-responsive materials and tip-mounted transducers, with soft bioinspired geometry and actuation mechanisms. This review aims to highlight the state of the art in the development of functionalized soft continuum robots for minimally invasive and endoluminal applications. Drawing on advances over the past twenty-five years, we provide a comprehensive discussion of the innovations to date and of the pivotal clinical and developmental challenges to be overcome for the functionalization, therapeutic benefit and therefore, clinical translation of soft continuum robots. Through developing coherence between the fields of bio-inspired soft robotic design, digitally driven fabrication, materials engineering and intra-operative control, further clinically significant advances may be realized in the domain of functionalized soft continuum robots
Duration and the prosodic disambiguation of nested structure
No full textDurational information provides strongly reliable cues for organizing and tracking syntactic structure of sentences. At the same time, durational properties of speech are largely dependent on complexity, often modelled as a function of predictability: higher predictability is reliably associated with shorter duration, while less predictable elements of utterances are more carefully articulated, and thus produced more slowly. While the two determinants of duration (structure and predictability) are often aligned, there exist a well-defined set of exceptions where the two factors make opposite predictions. We discuss converging evidence that rhythm modulation might play a crucial role in the disambiguation of structural nesting, leading to shorter duration for more complex nested structures and longer duration for simpler structures involving sisterhood. We then present an account of these durational differences and rhythmic patterns, based on the interaction of independently motivated prosodic principles
Online Task-Free Continual Learning via Expansible Vision Transformer
Get PDFVision Transformers (ViTs) have lately shown remarkable data representation capabilities leading to state-of-the-art results in several vision and language learning tasks. Given its powerful representation ability, some recent studies have explored the ViT in continual learning by employing the dynamic expansion mechanism. However, these methods rely on the task information and therefore can not deal with a more realistic scenario, namely the Task-Agnostic Continual Learning (TACL). Unlike these ViT-based continual learning methods, this paper addresses TACL by proposing the Lifelong Expansible Vision Transformer (LEViT) model, which dynamically increases the model’s capacity to deal with changes in the underlying probability distribution of the data representations learnt during continual learning. LEViT is implemented by an ensemble of transformers, each enabled with a multi-head attention mechanism and a linear classifier. We propose a new dynamic expansion mechanism which incrementally increases the capacity of LEViT without requiring task labels, by evaluating the statistical similarity between the joint distribution modeled by all previously learned components and the probabilistic representation of incoming data samples. The proposed expansion mechanism ensures the diversity of learnt knowledge by the components of LEViT. In addition, we introduce the Dynamic Knowledge Fusion (DKF) approach, aiming to explore the ViT feature representation ability for knowledge transfer. Specifically, we view all previously learnt components as an evolved knowledge base which provides prior knowledge for future learning. The proposed LEViT, when compared to the existing ViT-based methods, does not require any task information and can reuse previously learned representations to promote future task learning
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