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Targeting the formyl peptide receptor 1 for treatment of glioblastoma
Get PDFBackground and Aims Gliomas account for over half of all primary brain
tumours and have a very poor prognosis, with a median survival of less than
two years. There is an urgent and unmet clinical need to develop new
therapies against glioma. Recent reports have indicated the overexpression of
FPR1 in gliomas particularly in high grade gliomas. The aim of this project was
to identify and synthesise small molecule FPR1 antagonists, and to
demonstrate a proof of principle in preclinical in vitro and in vivo models that
small molecule FPR1 antagonism can retard expansion of glioma.
Methods A number of small molecule FPR1 antagonists were identified by
in silico design, or from the literature and then were prepared using chemical
synthesis. FPR1 antagonists were evaluated in vitro for their ability to abrogate
FPR1-induced cellular responses in a range of models including calcium
mobilisation, cell migration, and invasion. The efficacy of FPR1 antagonist
ICT12035 in vivo was assessed in a U-87 MG subcutaneous xenograft model.
Results Virtual high throughput screening using a homology model of
FPR1 led to the identification of two small molecule FPR1 antagonists. At the
same time chemical synthesis of two other antagonists, ICT5100 and
ICT12035 as well as their analogues were carried out. The FPR1 antagonists
were assessed in calcium flux assay which gave an insight into their structure-activity
relationship. Further investigation of both ICT5100 and ICT12035
demonstrated that both small molecule FPR1 antagonists were effective at
abrogating FPR1-induced calcium mobilisation, migration, and invasion in U-
87 MG in vitro models in a dose-dependent manner. ICT12035 is a particularly
selective and potent inhibitor of FPR1 with an IC50 of 37.7 nM in calcium flux
assay. Additionally, it was shown that the FPR1 antagonist ICT12035 was able
to arrest the growth rate of U-87 MG xenografted tumours in mice.
Conclusion The results demonstrate that targeting FPR1 by a small
molecule antagonist such as ICT12035, could provide a potential new therapy
for the treatment of glioblastoma.Yorkshire Cancer Researc
How can the potential of the duocarmycins be unlocked for cancer therapy?
No full textNoThe duocarmycins belong to a class of agent that has fascinated scientists for over four decades. Their exquisite potency, unique mechanism of action, and efficacy in multidrug-resistant tumour models makes them attractive to medicinal chemists and drug hunters. However, despite great advances in fine-tuning biological activity through structure-activity relationship studies (SARS), no duocarmycin-based therapeutic has reached clinical approval. In this review, we provide an overview of the most promising strategies currently used and include both tumour-targeted prodrug approaches and antibody-directed technologies
Proteomic profiling of matched normal and tumour tongue biopsies from smokers and non-smokers. Oncoproteomic applications for oral tongue squamous cell carcinoma biomarker discovery
No full textDespite considerable development in the therapeutic repertoire for managing cancer-related malignancies, head and neck cancer mortality has not significantly improved. The burden of HNSCC fluctuates across countries and has been associated with exposure to tobacco-derived carcinogens, excessive alcohol consumption or combinations. Due to late detection, patients often present with oral pre-malignant lesions which have progressed to an advanced stage of HNSCC. In this study, the samples were from a male cohort as generally, men are at two to four-fold higher risk than women with over 90% of HNSCCs arising in the upper aerodigestive tract. Therefore, the purpose of this thesis was to identify HNSCC biomarkers in males associated within defined anatomical region (tongue) and causative agents, specific to smoking.
An iTRAQ proteomic approach was used to profile protein changes in matched normal and tumour samples from male non-smoking (n=6) and smoking patients (n=6) with tongue carcinomas revealing identification of potential targets specific to cancer. Samples were subjected to liquid nitrogen cryo-pulverisation and protein determination. Protein extracts from the same category were pooled, trypsin digested and iTRAQ 4-plex labelled. Data was generated by 2D-LC/MS on an Orbitrap Fusion and significantly changed proteins (median ± SD) were subject to bioinformatics appraisal. A total of 3426 proteins were identified and quantified by proteomic analysis. Comparison of non-smoker tumour (NS:T) with smoker tumour (S:T) distinguished 64 proteins that were upregulated and 62 downregulated, S:T vs S:N categorised 349 proteins up- and 395 down-regulated respectively and NS:T vs NS:N identified 469 proteins up- and 431 down-regulated, respectively. Arginase-1 (ARG1), Keratin Type-2 Cytoskeletal 8 (KRT8), Lipocalin-1 (LCN1) and DNA replication licensing factor MCM2 (MCM2) were identified as biologically associated with smoking compared to non-smoking, providing viable targets for verification by immunochemical methods which further supported the proteomic data.
Overall, the project demonstrated the importance of using matched biopsies with good clinicopathological data for experimental design and provided a set of unique targets for a more expanded verification study
A mussel-inspired antibacterial hydrogel with high cell affinity, toughness, self-healing, and recycling properties for wound healing
No full textYesAntibacterial hydrogels have been intensively studied due to their wide practical potential in wound healing. However, developing an antibacterial hydrogel that is able to integrate with exceptional mechanical properties, cell affinity, and adhesiveness will remain a major challenge. Herein, a novel hydrogel with antibacterial and superior biocompatibility properties was developed using aluminum ions (Al3+) and alginate−dopamine (Alg-DA) chains to cross-link with the copolymer chains of acrylamide and acrylic acid (PAM) via triple dynamic
noncovalent interactions, including coordination, electrostatic interaction, and hydrogen bonding. The cationized nanofibrillated cellulose (CATNFC), which was synthesized by the grafting of long-chain quaternary ammonium salts onto nanofibrillated cellulose (NFC), was utilized innovatively in the preparation of antibacterial hydrogels. Meanwhile, alginate-modified dopamine (Alg-DA) was prepared from dopamine (DA) and alginate. Within the hydrogel, the catechol groups of Alg-DA provided a decent fibroblast cell adhesion to the hydrogel. Additionally, the multitype cross-linking structure within the hydrogel rendered the outstanding mechanical properties, self-healing ability, and recycling in pollution-free ways. The antibacterial test in vitro, cell affinity, and wound healing proved that the as-prepared hydrogel was a potential material with all-around performances in both preventing bacterial infection and promoting tissue regeneration during wound healing processes.National Natural Science Foundation of China (32070826 and 51861165203), the Chinese Postdoctoral Science Foundation (2019M650239, 2020T130762), the Sichuan Science and Technology Program (2019YJ0125), the State Key Laboratory of Polymer Materials Engineering (sklpme2019-2-19), the Chongqing Research Program of Basic Research and Frontier Technology (cstc2018jcyjAX0807), Chongqing Medical Joint Research Project of Chongqing Science and Technology Committee & Health Agency (2020GDRC017), and the RCUK China-UK Science Bridges Program through the Medical Research Council, and the Fundamental Research Funds for the Central Universitie
Constitutive modelling of polylactic acid at large deformation using multiaxial strains
No full textYesSheet specimens of a PLLA-based polymer have been extended at a temperature near to the glass transition in both uniaxial and planar tension, with stress relaxation observed for some time after reaching the final strain. Both axial and transverse stresses were recorded in the planar experiments. In all cases during loading, yielding at small strain was followed by a drop in true stress and then strain hardening. This was followed by stress relaxation at constant strain, during which stress dropped to reach an effectively constant level. Stresses were modelled as steady state and transient components. Steady-state components were identified with the long-term stress in stress relaxation and associated with an elastic component of the model. Transient stresses were modelled using Eyring mechanisms. The greater part of the stress during strain hardening was associated with dissipative Eyring processes. The model was successful in predicting stresses in both uniaxial and planar extension over a limited range of strain rate
Neuroevolutionary intelligent system to aid diagnosis of motor impairments in children
No full textNoAn early detection of motor impairments in children is essential to improve self-care. Nevertheless, it may not be straightforward to conduct all required assessments physically in a clinic. Previous efforts in providing such a classification leveraged Machine Learning (ML)-based techniques on centralised data collected from activities of daily living (ADL); however, they used black-box optimisation methods and classification approaches that are not generalisable, hindering their application and impact in a clinical setting from an applied intelligence perspective. Thus, this study developed, applied, and validated a novel two-step neuroevolutionary optimisation approach to achieve earlier convergence in a user-centred and explainable manner, by applying early stopping based on three cross-entropy loss functions (for training, validation, and test) and optimise hyperparameters concurrently to ensure generalisation of the predictive performance by design. This method was applied to a neural network-based decision support system for aiding detection of motor impairments using three publicly available datasets on 190 children with motor impairments, including 483 socio-demographic and clinical self-care-related features in total. Such biomarkers were based on “The International Classification of Functioning, Disability, and Health for Children and Youth” (ICF-CY) and retrieved from the University California Irvine ML database, which were leveraged for the initial model training, validation, and testing. Moreover, to increase users’ confidence and drive adoption of the proposed applied intelligence-based tool, two additional publicly available datasets were used for validating the proposed two-step neuroevolutionary approach; such data include 34 and 39 socio-demographic and self-care-related clinical characteristics features as indicators of the functional independence of 50 further children with motor disability from a hospital in the city of Salvador, State of Bahia in Brazil. A novel, explainable and generalisable two-step neuroevolutionary approach guided early stopping based on three cross-entropy loss functions and optimised hyperparameters concurrently to improve generalisation in a neural network-based classifier. The ability of the proposed hybrid decision support system to detect motor impairments in the paediatric subjects considered was evaluated as compared to the best-performing ML-based classification systems on the same benchmark datasets to date. Whilst leveraging a transparent optimisation approach, results demonstrate its superior generalisation, quantified via the classification accuracy and the area under the receiver operating characteristic curve, being almost 6% higher than the most accurate and reliable ML-based system on the same benchmark dataset from published studies, thus supporting its potential for aiding classification of self-care problems in children with physical and motor disability in a clinical setting
Optimal Energy Resource Allocation in Isolated Micro Grid with Limited Supply Capacity
No full textNoAn isolated micro-grid network with limited generating capacity would most likely, end up having operational challenge either due to increasing number of customers, or introduction of new loads onto the network. This is in view of an observed scenario especially in developing countries whereby as load demand increases, installed PV capacity often do not receive commensurate expansion. So, in order to prevent network failure, each user can be allocated certain amount of limited power supply which should not be exceeded. These allotments are dynamic, and they vary at regular time intervals every day depending on their historic load profile data. This work is therefore based on managing power supply from a PV-source operating as an isolated micro-grid with storage capabilities. A power supply scheduling mechanism is introduced which allocates maximum power capacity for every user. Hence communities detached from the grid can enjoy electricity despite shortfalls in power supply capacity. The obtained results evaluated under three scenarios show that allocating energy limits to each user depends on the current capacity of the battery as well as the forecast load demand. This allotment is enforced using variable circuit breakers whose cut-off point is varied based on the prevailing energy demand and supply requirements
Self-Preservation of Turbulence Statistics in the Wall-Wake Flow of a Bed-Mounted Horizontal Pipe
No full textYesThis research article analyzed the self-preserving behaviour of wall-wake region of a circular pipe mounted horizontally over a flat rigid sand bed in a shallow flow in terms of mean velocity, RSS, and turbulence intensities. The study aims to investigate self-preservation using appropriate length and velocity scales.in addition to that wall-normal distributions of the third-order correlations along the streamwise direction in the wake region are analyzed. An ADV probe was used to record the three-dimensional instantaneous velocities for four different hydraulic and physical conditions corresponding to four cylinder Reynolds numbers. The results revealed that the streamwise velocity deficits, RSS deficits, and turbulence intensities deficits distributions displayed good collapse on a narrow band when they were non-dimensionalized by their respective maximum deficits. The wall-normal distance was non-dimensionalized by the half velocity profile width for velocity distributions, while the half RSS profile width was used in the case of the RSS deficits and turbulence intensities deficits distributions. The results indicate the self-preserving nature of streamwise velocity, RSS, and turbulence intensities in the wall-wake region of the pipe. The third-order correlations distributions indicate that sweep is the dominant bursting event in the near-bed zone. At the same time, ejection is the dominant bursting event in the region above the cylinder height
Numerical investigation of the influence of the small pipeline on local scour morphology around the piggyback pipeline
No full textYesThis paper presents the results from a numerical simulation study to investigate the effect of the position angle (α) of small pipeline on the local scour and the hydrodynamic force around the piggyback pipeline in steady current conditions. Results show that the local scour depth around the piggyback pipeline increases first and then decreases with the increase of α. The scour depth and width reach the maximum values as the small pipe locates at the top of the large pipeline (i.e. α = 90°). The scour around the piggyback pipeline is accelerated when α ranges between 30° and 165°, while for α = 0°–30° and 165°–180°, the local scour around the piggyback pipeline is inhibited. Furthermore, the small pipe placed in front of the large pipe has slightly larger effect on the scour hole morphology than that when it is placed behind the large pipe. The drag force coefficient increases first and reaches the maximum value at α = 75°, and then decreases with the increase of α. Eventually the drag force coefficient approaches roughly a constant. The lift force coefficient is approximately a V-shaped with the variation of α and has the maximum value at α = 90°
Flood Suspended Sediment Transport: Combined Modelling from Dilute to Hyper-concentrated Flow
No full textYesDuring flooding, the suspended sediment transport usually experiences a wide-range of dilute to hyper-concentrated suspended sediment transport depending on the local flow and ground con-ditions. This paper assesses the distribution of sediment for a variety of hyper-concentrated and dilute flows. Due to the differences between hyper-concentrated and dilute flows, a linear-power coupled model is proposed to integrate these considerations. A parameterised method combining the sediment size, Rouse number, mean concentration, and flow depth parameters has been used for modelling the sediment profile. The accuracy of the proposed model has been verified against the reported laboratory measurements and comparison with other published analytical methods. The proposed method has been shown to effectively compute the concentration profile for a wide range of suspended sediment conditions from hyper-concentrated to dilute flows. Detailed com-parisons reveal that the proposed model calculates the dilute profile with good correspondence to the measured data and other modelling results from literature. For the hyper-concentrated profile, a clear division of lower (bed-load) to upper layer (suspended-load) transport can be observed in the measured data. Using the proposed model, the transitional point from this lower to upper layer transport can be calculated precisely