In-situ Analysis of Nanoscale Deformation Mechanism in Mutable Collagenous Tissue

PhDEchinoderms, for example sea cucumber, contain a unique collagenous tissue, with special biomechanical properties, which could near-instantly change their mechanical state (going from stiff to soft, and vice versa, in less than a second). However, the structure-function relation has so far not been exploited. Understanding how the material design of mutable collagenous tissue (MCT) enables this remarkable dynamical mechanical behaviour will help enable development of new biomaterials with adaptable mechanical properties. Currently, it is hypothesised that MCT can rapidly form crosslinks between the collagen fibrils and stiffen the interfibrillar matrix under neural control, but this had never been shown directly. In this thesis, we carried out an experimental study of quantifying how the interfibrillar matrix response to stimuli agents, to generate active forces and change conformation using a synchrotron in situ X-ray nanomechanical imaging method. By the uncovering of the mechanisms of active force generation, a valuable guideline, which could be applied in bioinspired constructs that response to external stimuli, can be obtained.School of Engineering and Materials Science (SEMS) at Queen Mary University of London Chinese Scholarship Counci

Interfibrillar stiffening of echinoderm mutable collagenous tissue demonstrated at the nanoscale

The mutable collagenous tissue (MCT) of echinoderms (e.g., sea cucumbers and starfish) is a remarkable example of a biological material that has the unique attribute, among collagenous tissues, of being able to rapidly change its stiffness and extensibility under neural control. However, the mechanisms of MCT have not been characterized at the nanoscale. Using synchrotron small-angle X-ray diffraction to probe time-dependent changes in fibrillar structure during in situ tensile testing of sea cucumber dermis, we investigate the ultrastructural mechanics of MCT by measuring fibril strain at different chemically induced mechanical states. By measuring a variable interfibrillar stiffness (E(IF)), the mechanism of mutability at the nanoscale can be demonstrated directly. A model of stiffness modulation via enhanced fibrillar recruitment is developed to explain the biophysical mechanisms of MCT. Understanding the mechanisms of MCT quantitatively may have applications in development of new types of mechanically tunable biomaterials

Revealing the microstructural stability of a three-phase soft solid (ice cream) by 4D synchrotron X-ray tomography

Understanding the microstructural stability of soft solids is key to optimizing formulations and processing parameters to improve the materials' properties. In this study, in situ synchrotron X-ray tomography is used to determine the temperature dependence of ice-cream's microstructural evolution, together with the underlying physical mechanisms that control microstructural stability. A new tomographic data processing method was developed, enabling the features to be segmented and quantified. The time-resolved results revealed that the melting-recrystallization mechanism is responsible for the evolution of ice crystal size and morphology during thermal cycling between −15 and −5 °C, while coalescence of air cells is the dominant coarsening mechanism controlling air bubble size and interconnectivity. This work also revealed other interesting phenomena, including the role of the unfrozen matrix in maintaining the ice cream's microstructural stability and the complex interactions between ice crystals and air structures, e.g. the melting and recrystallization of ice crystals significantly affect the air cell's morphology and the behavior of the unfrozen matrix. The results provide crucial information enhancing the understanding of microstructural evolution in multi-phase multi-state complex foodstuffs and other soft solids

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

Energy, Economic, and Environmental Assessment of Sweet Potato Production on Plantations of Various Sizes in South China

Sweet potato (Ipomoea batatas L.) is an important starch-producing crop used worldwide. However, few studies have been conducted on the energy efficient, cost benefit, and greenhouse gas (GHG) emissions of sweet potato production. To address this issue, the data were collected using a questionnaire for face-to-face interviews of 78 sweet potato growers and 74 reference crop (i.e., rice, maize, and potato) growers in Guangdong province. Results revealed that sweet potato production exhibited the highest value of energy efficiency (0.83 kg MJ−1) and economic productivity (0.85 kg CNY−1) among four crops. The GHG emissions from sweet potato production (1165 kg CO2-eq ha−1) were significantly higher than GHG from rice and maize but lower than GHG from potatoes. Moreover, plantation size significantly (p −1) and the lowest GHG emissions (1045 kg CO2-eq ha−1). Quartering assessments based on energy efficiency, economic productivity, and GHG emissions showed that fertilizers and labor were the major contributors to energy consumption, economic costs, and GHG emissions. Future efforts should be made to reduce fertilizer application and increase fertilizer use efficiency for sustainable sweet potato production

Time-Variant Reliability Optimization for Stress Balance in Press-Pack Insulated Gate Bipolar Transistors

Stress imbalance significantly affects the performance of a press-pack insulated gate bipolar transistor (IGBT). Time-variant loads and conditions lead to the stress fluctuations, exacerbating the impacts. The conventional reliability optimization faces efficiency barriers due to the nested time-variant reliability analysis and design optimization. In this paper, a time-variant reliability optimization approach for press-pack IGBTs is proposed to address the efficiency issue of the IGBT reliability optimization. The performance functions of the maximum and typical stresses are formulated as the optimization objective and constraint. A time-variant reliability optimization model is formulated considering the stress balance reliability degradation within the service cycle. A decoupling algorithm is proposed to transform the nested optimization into a sequential iteration of static reliability optimization and time-variant reliability analysis. The reliability analysis utilizes the performance function continuity in the time domain to reduce the evaluations for the most likelihood points, thereby enhancing efficiency. Numerical and experimental results on an actual IGBT demonstrate the accuracy of the stress balance performance analysis. The time-variant reliability optimization based on the performance functions improves the stress balance performance by 16.3&#x0025; and meets the reliability requirements within the service cycle. Compared with the conventional double-loop approach, the difference between the solution of the proposed approach with the reference solution is 0.4&#x0025;, and the efficiency is 334 times that of the double-loop approach. The performance advantages in accuracy and efficiency exhibit the application potential of this approach

Advancing the local climate zones framework: A critical review of methodological progress, persisting challenges, and future research prospects

The local climate zones (LCZs) classification system has emerged as a more refined method for assessing the urban heat island (UHI) effect. However, few researchers have conducted systematic critical reviews and summaries of the research on LCZs, particularly regarding significant advancements of this field in recent years. This paper aims to bridge this gap in scientific research by systematically reviewing the evolution, current status, and future trends of LCZs framework research. Additionally, it critically assesses the impact of the LCZs classification system on climate-responsive urban planning and design. The findings of this study highlight several key points. First, the challenge of large-scale, efficient, and accurate LCZs mapping persists as a significant issue in LCZs research. Despite this challenge, the universality, simplicity, and objectivity of the LCZs framework make it a promising tool for a wide range of applications in the future, especially in the realm of climate-responsive urban planning and design. In conclusion, this study makes a substantial contribution to the advancement of LCZs research and advocates for the broader adoption of this framework to foster sustainable urban development. Furthermore, it offers valuable insights for researchers and practitioners engaged in this field.Design & Construction Managemen