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Developing a gene therapy for Stargardt Disease
Get PDFStargardt disease was first described by Stargardt in Bonn in 1909 and is the most common recessively inherited macular degeneration, affecting 1:8,000-10,000. It results in progressive vision loss and legal blindness by the fourth to seventh decade of life, therefore, it is highly clinically relevant. Stargardt disease is caused by mutations in the ABCA4 gene, which encodes the ATP-binding Cassette protein -4 (ABCA4), a transport protein essential to the visual cycle which is expressed in photoreceptor outer segments.Gene therapy has shown promise in treating autosomal recessive or X-linked inherited retinal degenerations, where genes can be packaged into the adeno-associated viral vector (AAV) capsid and delivered to target cells. However, the packaging capacity of AAV is ~4.7kb and thus, at 6.8kb, ABCA4 is too large for AAV gene supplementation therapy. Novel CRISPR technologies, such as DNA and RNA base editing, enable correction of pathogenic transition mutations (A-G, C-T). ABCA4 has ~1200 known pathogenic mutations of which 63% are editable transition mutations. In this thesis, I explore and compare the therapeutic potential of CRISPR-Cas mediated DNA and RNA base editing of ABCA4.First, the experiments reported in this thesis investigated the relevance of DNA and RNA base editors in targeting ABCA4 by analysing multiple online databases and clinical cohorts. In particular, the PAM-site requirement of DNA base editors was investigated and determined to not be a limiting factor due to the high degree of heterogeneity observed in ABCA4. Following the screen, a clinically relevant nonsense mutation, c.206 G>A (W69*) in ABCA4 was targeted by both an SaKKHABE8e DNA base editor and dPspCas13b-ADARDD RNA base editor in vitro, and analysed at the DNA, RNA, and protein level. I demonstrated robust and targeted editing by both DNA and RNA base editors that resulted in production of full-length ABCA4 protein.This work went on to evaluate the AAV-delivered SaKKHABE8e DNA base editor and dPspCas13b-ADARDD RNA base editor in complex pre-clinical models, including in a mouse model and in retinal organoids, to establish the translational capabilities of the editors in the retina targeting ABCA4. Initially, both models were to contain the patient c.93 G>A nonsense mutation, however, production of both models is still ongoing and was thus not possible to target within this thesis. Instead, after in vitro screens, the base editors were used to knockdown ABCA4 in vivo and target a mutation near c.93 in retinal organoids to evaluate base editor efficacy across models and across target sites. I demonstrated that for dCas13b-ADARDD there is a large discrepancy in editing efficiencies between in vitro data and the complex models. Further, I successfully used SaKKHABE8e in vivo by AAV delivery to specifically and robustly target the ABCA4 start codon. This represents the first use of the single AAV all-in-one SaKKHABE8e in photoreceptors
Rapid and robust microstructural imaging with diffusion MRI
Get PDFDiffusion magnetic resonance imaging (dMRI) provides an non-invasive way to detect tissue microstructure information by probing the Brownian motion of water molecules and estimating the diffusion properties using signal analysis models. dMRI is broadly used in neuro disease detection and basic neuroscience studies. The most widely used dMRI acquisition technique is a two-dimensional (2D) single-shot echo planar imaging sequence due to its rapid acquisition speed. Recently, many advanced diffusion analysis models have been proposed which offer more specific estimates of tissue biophysical properties from acquired dMRI signals compared to simpler models like diffusion tensor imaging (DTI). However, these analysis models require acquisition of large numbers of diffusion volumes, which increases the dMRI scan time significantly and hinders their wider in vivo applications. Many efforts have been made to develop acquisition and reconstruction methods for fast dMRI scans, yet the trade-off between scan time, spatial resolution and model specificity still remains as a major challenge for dMRI studies. The works in this thesis aim to develop acquisition and reconstruction methods that allow for rapid and robust brain microstructural imaging with dMRI. Firstly, a joint k-q reconstruction method based on Gaussian process is developed for accelerating multi-shell dMRI acquisition. Secondly, a computationally efficient eddy current and motion robust joint k-q reconstruction method is developed to increase the robustness of the joint reconstruction methods when the subjects may be uncooperative during scans. Thirdly, we extend the previous methods to accelerate diffusion-relaxometry imaging for microstructural imaging with higher specificity by using a k-q-TE joint acquisition and reconstruction method. The methods developed in this thesis seek to reduce the dMRI scan time while preserve the image quality and analysis accuracy, which offers potential to enable advanced microstructural imaging within clinically feasible time
Classification of finite depth objects in bicommutant categories via anchored planar algebras
Get PDFIn our article [arXiv:1511.05226], we studied the commutant C′ ⊂ Bim(R) of a unitary fusion category C, where R is a hyperfinite factor of type II1, II∞, or III1, and showed that it is a bicommutant category. In other recent work [arXiv:1607.06041, arXiv:2301.11114] we introduced the notion of a (unitary) anchored planar algebra in a (unitary) braided pivotal category D, and showed that they classify (unitary) module tensor categories for D equipped with a distinguished object. Here, we connect these two notions and show that finite depth objects of C′ are classified by connected finite depth unitary anchored planar algebras in Z(C). This extends the classification of finite depth objects of Bim(R) by connected finite depth unitary planar algebras
Modulating Redox Mechanism in Metal Chalcogenides by Precisely Controlling Phase Transition to Achieve Ultrafast and Ultra‐Stable Sodium‐Ion Batteries
Get PDFMetal chalcogenides represent promising anodes for sodium‐ion batteries due to their high theoretical capacities and low material costs. However, their practical applications are hampered by inherently sluggish ion diffusion kinetics and severe volume expansion associated with their conventional conversion reaction mechanism. Here, we design a micro‐nano ZnS/ZnSe heterostructured anode through in situ localized phase transformation strategy. This meticulously engineered architecture effectively modulates the Na+ storage mechanism from a typical conversion reaction to the surface redox pseudocapacitive reaction by precisely controlling the phase transition processes. Such structural control substantially increases Na+ diffusion sites and reconstructs internal electric fields. Moreover, abundant heterointerfaces and porous microstructure effectively alleviate internal mechanical stresses, provide a large number of Na+ storage sites and fast Na+ migration channels, collectively ensuring ultrafast reaction kinetics and superior structural stability of the ZnS/ZnSe. As a result, the ZnS/ZnSe exhibits a remarkable specific capacity of 796 mAh g−1 at 0.1 A g−1, stable cycling with no capacity decay over 1800 cycles at 15 A g−1, and capacity retention of 89% even at ultrahigh current density of 20 A g−1. Furthermore, the practical viability of this material is successfully demonstrated in a NaNi1/3Fe1/3Mn1/3O2(NFM)//ZnS/ZnSe full‐cell, which shows outstanding cycling stability without noticeable capacity fading after 600 cycles
Reference charts for first‐trimester placental three‐dimensional fractional moving blood volume derived using OxNNet
Get PDFObjective: To establish a comprehensive reference range for first‐trimester placental three‐dimensional (3D) single‐vessel fractional moving blood volume (svFMBV) using the OxNNet toolkit, based on values observed in healthy pregnancies. Methods: This study utilized data from the First‐trimester Placental Ultrasound (FirstPLUS) study, a longitudinal observational cohort study conducted between March and November 2022 at King's College Hospital, London, UK. Participants underwent 3D ultrasound assessment of the placenta, including power Doppler imaging, during routine first‐trimester screening. The OxNNet toolkit was used for automated placental segmentation and 3D‐svFMBV calculation. Quality control was performed in three stages to ensure image completeness and segmentation accuracy. Quantile regression and lambda‐mu‐sigma (LMS) modeling were used to construct reference charts for 3D‐svFMBV. Model fit was assessed using the Akaike information criterion, and centile curves were constructed. Results: The final cohort comprised 2547 cases. Visual assessment of histograms and quantile−quantile plots revealed positive skew in 3D‐svFMBV determined at five specific locations within the uteroplacental vasculature. LMS modeling provided the best fit for constructing centile charts, with the Box–Cox Power Exponential original distribution used in most cases. The resulting centile charts demonstrated close agreement between predicted and observed centiles, with minimal deviation across all target centiles. Conclusions: This study provides novel reference ranges for first‐trimester placental 3D‐svFMBV at five locations within the uteroplacental vasculature. These findings offer a valuable foundation for future research into placental function and pregnancy outcome. © 2026 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology
Proteome constrained metabolic modeling of Sus scrofa muscle stem cells for cultured meat production
Get PDFCultured meat has recently emerged as a sustainable alternative to traditional livestock farming and gained attention as a promising future protein source. Herein, the Sus scrofa muscle stem cell is a commonly used cell source in the cell proliferation step of cultured meat production. However, a major bottleneck of large-scale cultivation is the inhibition by secreted and accumulated lactate and ammonium in the process of S. scrofa cell proliferation. To simulate the growth and metabolism of S. scrofa muscle stem cells under different lactate and ammonium concentrations, this study constructed the first proteome constrained metabolic model for the core metabolism of S. scrofa muscle stem cells, pcPigMNet 2025. The relationship of lactate and ammonium levels with cellular metabolism was derived from growth and metabolomics data of two culture conditions with low and high initial ammonium concentrations, and then incorporated into metabolic flux simulation. Metabolic flux simulations for experimental conditions, along with perturbation simulations considering stressed non-growth associated maintenance and oxygen supply, demonstrated that pcPigMNet2025 could effectively characterize the response of the S. scrofa muscle stem cell's growth and metabolism to varying environmental conditions, shedding light on model-aided control and optimization of the cultured meat production process
Public attitudes towards consent for the donation of surplus frozen eggs to research
Get PDFStudy question: In the context of donating Surplus Frozen Eggs (SFE) to research, what level of information disclosure, and associated consent model, do the public believe most effectively allows donors to make an informed decision, exercise autonomy, and be treated morally?Summary answer: The public supports the information disclosure requirements of both a specific and broad consent model in this context, with the latter considered to better enhance autonomy and facilitate the moral treatment of SFE donors.What is known already: Despite research indicating that many individuals’ first preference is to donate their SFEs to research, donation rates remain low. One possible reason for this is the way consent processes for the donation of SFEs to research are currently regulated, specifically that their high information requirements limit opportunities to donate. There is a notable lack of research on how consent processes should operate, and more specifically, how much information a person should be provided before providing consent, in the context of donating SFEs to research.Study design, size, duration:An online experimental survey of 225 participants was conducted. The survey assessed the impact of two variables – Information Disclosure and Preference Fulfilment – on participants' views towards whether a consent process allowed for informed, autonomous consent and the moral treatment of donors.Participants/materials, setting, methods:A nationally representative sample of the United Kingdom (UK) public was recruited using the online platform Prolific. The survey consisted of a vignette-based experimental design, one free-text question, and demographic data collection. Quantitative data were summarised using descriptive statistics and the relationship between variables were tested using ANOVAs and t-tests, where appropriate. Inductive content analysis through manual coding was performed on the free-text question.Main results and the role of chance: Participants considered both specific and broad information disclosure as sufficient for informed consent (mean Consent Judgements M=6.49/7 and M=5.79/7 respectively). The ability to fulfil disposition preferences was critical to the public’s assessment of whether a consent process enabled donors to act autonomously and be treated morally. Participants agreed that a potential donor was able to make an autonomous decision if their preference to donate their SFEs to research was fulfilled (mean Autonomy Judgement M=5.46/7, mean Moral Judgement M=5.63/7), but not when it was not (mean Autonomy Judgement M=3.96/7, mean Moral Judgement: M=4.76/7).Limitations, reasons for caution:Ecological validity of online surveys is limited, and data may be subject to response biases. Additionally, the sample size was relatively small. Finally, since the sample population wasbased in the UK, the generalisability of the survey findings to other countries may be limited.Wider implications of the findings:Our findings underscore the need to review and possibly update consent processes for the donation of SFEs to research. We encourage policy discussion in light of our findings, specifically the consideration of a shift towards a broad consent model. Doing so may allow more donors to fulfil their disposition preference, facilitate the movement of SFEs out of storage, and respond to the shortage of eggs currently available for research
The geography of financial integration: regional disparities in Italian correspondent banking with London, 1920-1985
No full textThis paper offers new micro-level evidence on how the structure of the Italian banking system evolved vis-à-vis banks in London. Our approach allows us to measure the pattern of thousands of bilateral payment connections between banks in Italy and London over the 20th century at a much more granular level than existing studies, which have focused on the business of large banks. We use the data to explore the regional and local geography of cross-border banking links. This reveals how smaller banks in towns and cities across Italy were connected to the global payment system to provide services to local migrants, traders, and investors. We find that the changing pattern of banks’ links to London over time did not merely reflect economic growth and suggest further avenues for analysis
Temperature-dependence of charge and exciton transport in one-dimensional systems subject to static and dynamic disorder
Get PDFThe temperature-dependence of dynamical properties (e.g., the asymptotic diusion coecient and the sub-diusive exponent) are calculated for charges and excitons in one-dimensional systems subject to static and dynamic disorder. These properties are determined by three complementary methods. One approach is via the time-integration of the velocity autocorrelation function. The second is via the mean-squared-displacement of thermal wavepackets subject to stochastic collapse via Lindblad jump operators. These two methods are applicable in the high-temperature regime, where the noise is temporally uncorrelated. In this regime the noise causes particle localization and the transport is diusive. The third approach applicable in the low-temperature regime is weak-coupling Redeld theory. Here, static disorder causes Anderson localization. When the dynamics is diusive, the diusion coe- cient is a non-monotonic function of temperature, increasing with temperature in the low-temperature Environment Assisted Quantum Transport (ENAQT) regime and decreasing with temperature in the high-temperature Quantum-Zeno (QZ) regime. For any temperature, static disorder decreases the diusion coecient. Increasing the dephasing factor increases the diusion coecient in the ENAQT regime, whereas the diusion coecient decreases in the QZ regime. The dynamics is non-diusive for thermal energies deep within the manifold of local-ground-states, where the subdiusive exponent decreases with increasing disorder and decreasing temperature
Pathogen-inspired engineering of plant protease enhances late blight resistance
Get PDFThe apoplast is an important battlefield in plant–pathogen interactions. The late blight oomycete pathogen Phytophthora infestans, for instance, secretes cystatin-like protease inhibitors EpiC1 and EpiC2B to suppress C14, a papain-like immune protease secreted by tomato. Here, we found that P. infestans also secretes two distinct papain-like proteases termed Pain1 and Pain2, which are transcriptionally induced during infection. Both Pains promote P. infestans infection, but not when their catalytic residues are mutated. Strikingly, EpiC1 and EpiC2B preferentially inhibit tomato C14 rather than self-produced Pains, suggesting that they coevolved with Pains to avoid self-inhibition. To mimic the avoidance of inhibition by EpiCs, we engineered C14 (eC14) with seven Pain1 residues that potentially disturb the EpiCs–C14 interface. This eC14 is less sensitive to inhibition by EpiCs and enhances resistance to P. infestans infection. This strategy demonstrates that a pathogen-inspired protein engineering approach can increase crop resistance to plant pathogens