University of Cambridge
  • Cambridge, United Kingdom
Recent publications
Stem cell-based transplantation is a promising therapeutic approach for intervertebral disc degeneration (IDD). Current limitations of stem cells include with their insufficient cell source, poor proliferation capacity, low nucleus pulposus (NP)-specific differentiation potential, and inability to avoid pyroptosis caused by the acidic IDD microenvironment after transplantation. To address these challenges, embryo-derived long-term expandable nucleus pulposus progenitor cells (NPPCs) and esterase-responsive ibuprofen nano-micelles (PEG-PIB) were prepared for synergistic transplantation. In this study, we propose a biomaterial pre-modification cell strategy; the PEG-PIB were endocytosed to pre-modify the NPPCs with adaptability in harsh IDD microenvironment through inhibiting pyroptosis. The results indicated that the PEG-PIB pre-modified NPPCs exhibited inhibition of pyroptosis in vitro; their further synergistic transplantation yielded effective functional recovery, histological regeneration, and inhibition of pyroptosis during IDD regeneration. Herein, we offer a novel biomaterial pre-modification cell strategy for synergistic transplantation with promising therapeutic effects in IDD regeneration.
Modelling the times-to-failures in industrial assets is critical for their maintenance planning. Modern fleets often comprise of clusters of similarly deteriorating assets, due to customisation or diversity in their operational settings. As such, the prevalent techniques of using a single fleet-wide model or independent cluster-specific models for modelling the times-to-failures are associated with high bias or high variance respectively. The problem of high variance is especially prominent for the asset clusters with where relatively fewer failures are observed. This paper proposes that statistical hierarchical modelling systematically mitigates the problem of high variance for the clusters with sparse data using shared higher level models for the cluster-specific model parameters. A hierarchical model of the Weibull density functions is shown in this chapter as an example because of the popularity of the Weibull distributions in reliability applications. Failure trajectories from a fleet of simulated turbofans are used herewith for the experiments that compare the advantage of the proposed hierarchical model over independent or fleet-wide models for modelling the observed times-to-failures.
Masonry arch bridges are numerous across European transportation networks. Many are ageing structures, with service lives of 100–150 years to date, and exhibit historic damage and repairs, leading to uncertainty regarding structural behaviour. For skewed bridges particularly, this can be complicated and three-dimensional, and detailed experimental data describing behaviour are rare. In 2018–2019, the authors deployed Fibre Bragg Grating (FBG) strain monitoring at a recently repaired, skewed masonry rail bridge in the UK. Following an on-site trial, the FBG monitoring system was substantially upgraded in 2020 to enable long-term, autonomous, remote sensing. This new system is introduced, including processes to automate data classification based on the date and time of measurements, and train class/operator, direction, and speed. This system has recorded the bridge responses to thousands of trains. Data analysis is presented, focusing particularly on seasonal and long-term variation of behaviour. Findings include the impact of ambient temperature; an inverse relationship is observed. Decreasing temperature causes thermal contraction of the masonry, allowing cracks to open and increasing the potential for bridge movements. After decoupling such effects, residual long-term changes may correspond to damage. Therefore, this system can provide valuable asset management information on the early onset of bridge deterioration.
The increasing global occurrence of recalcitrant multi-drug resistant Klebsiella pneumoniae infections warrants the investigation of alternative therapy options, such as the use of monoclonal antibodies (mAbs). We used a target-agnostic phage display approach to K. pneumoniae bacteria lacking bulky, highly variable surface polysaccharides in order to isolate antibodies targeting conserved epitopes among clinically relevant strains. One antibody population contained a high proportion of unique carbohydrate binders, and biolayer interferometry revealed these antibodies bound to lipopolysaccharide (LPS). Antibodies that bound to O1 and O1/O2 LPS were identified. Antibodies were found to promote opsonophagocytic killing by human monocyte-derived macrophages and clearance of macrophage-associated bacteria when assessed using high-content imaging. One antibody, B39, was found to protect mice in a lethal model of K. pneumoniae pneumonia against both O1 and O2 strains when dosed therapeutically. High-content imaging, western blotting and fluorescence-activated cell sorting were used to determine binding to a collection of clinical K. pneumoniae O1 and O2 strains. The data suggests B39 binds to D-galactan-I and D-galactan-II of the LPS of O1 and O2 strains. Thus, we have discovered an mAb with novel binding and functional activity properties that is a promising candidate for development as a novel biotherapeutic for the treatment and prevention of K. pneumoniae infections.
Therapeutic monoclonal antibodies and their derivatives are key components of clinical pipelines in the global biopharmaceutical industry. The availability of large datasets of antibody sequences, structures, and biophysical properties is increasingly enabling the development of predictive models and computational tools for the "developability assessment" of antibody drug candidates. Here, we provide an overview of the antibody informatics tools applicable to the prediction of developability issues such as stability, aggregation, immunogenicity, and chemical degradation. We further evaluate the opportunities and challenges of using biopharmaceutical informatics for drug discovery and optimization. Finally, we discuss the potential of developability guidelines based on in silico metrics that can be used for the assessment of antibody stability and manufacturability.
As our understanding of the importance of the human microbiota in health and disease grows, so does our need to carefully resolve and delineate its genomic content. 16S rRNA gene-based analyses yield important insights into taxonomic composition, and metagenomics-based approaches reveal the functional potential of microbial communities. However, these methods generally fail to directly link genetic features, including bacterial genes and mobile genetic elements, to each other and to their source bacterial genomes. Further, they are inadequate to capture the microdiversity present within a genus, species, or strain of bacteria within these complex communities. Here, we present a method utilizing fluorescence-activated cell sorting for isolation of single bacterial cells, amplifying their genomes, screening them by 16S rRNA gene analysis, and selecting cells for genomic sequencing. We apply this method to both a cultured laboratory strain of Escherichia coli and human stool samples. Our analyses reveal the capacity of this method to provide nearly complete coverage of bacterial genomes when applied to isolates and partial genomes of bacterial species recovered from complex communities. Additionally, this method permits exploration and comparison of conserved and variable genomic features between individual cells. We generate assemblies of novel genomes within the Ruminococcaceae family and the Holdemanella genus by combining several 16S rRNA gene-matched single cells, and report novel prophages and conjugative transposons for both Bifidobacterium and Ruminococcaceae. Thus, we demonstrate an approach for flow cytometric separation and sequencing of single bacterial cells from the human microbiota, which yields a variety of critical insights into both the functional potential of individual microbes and the variation among those microbes. This method definitively links a variety of conserved and mobile genomic features, and can be extended to further resolve diverse elements present in the human microbiota.
In all domains of life, RNA chaperones safeguard and guide the fate of the cellular RNA pool. RNA chaperones comprise structurally diverse proteins that ensure proper folding, stability, and ribonuclease resistance of RNA, and they support regulatory activities mediated by RNA. RNA chaperones constitute a topologically diverse group of proteins that often present an unstructured region and bind RNA with limited nucleotide sequence preferences. In bacteria, three main proteins - Hfq, ProQ, and CsrA - have been shown to regulate numerous complex processes, including bacterial growth, stress response and virulence. Hfq and ProQ have well-studied activities as global chaperones with pleiotropic impact, while CsrA has a chaperone-like role with more defined riboregulatory function. Here, we describe relevant novel insights into their common features, including RNA binding properties, unstructured domains, and interplay with other proteins important to RNA metabolism.
Although monoclonal antibodies have greatly improved cancer therapy, they can trigger side effects due to on-target, off-tumor toxicity. Over the past decade, strategies have emerged to successfully mask the antigen-binding site of antibodies, such that they are only activated at the relevant site, for example, after proteolytic cleavage. However, the methods for designing an ideal affinity-based mask and what parameters are important are not yet well understood. Here, we undertook mechanistic studies using three masks with different properties and identified four critical factors: binding site and affinity, as well as association and dissociation rate constants, which also played an important role. HDX-MS was used to identify the location of binding sites on the antibody, which were subsequently validated by obtaining a high-resolution crystal structure for one of the mask-antibody complexes. These findings will inform future designs of optimal affinity-based masks for antibodies and other therapeutic proteins.
Water is crucial for birds, especially during hot weather. However, the availability of water, and its use by birds in modern anthropogenic habitats, is far from understood, especially outside arid regions. Here, we analyze a large nationwide dataset collected in the temperate zone and present an overview of small water resources used by birds in urban and rural habitats in Poland. We investigated the proportion of birds using free-standing water, preferences for various water sources, and factors and threats influencing drinking and bathing behaviour. Birds using water resources are represented by various taxonomic and ecological groups. Species composition differed slightly due to environmental conditions in the vicinity of the water resource and the background species composition. In total 51 species were observed using water, representing 64% of the 80 species recorded in the vicinity. The probability of water usage was positively related to temperature, which further emphasizes the importance of water under future climate-warming scenarios. We show that small water resources, including those provided by people, were less likely to be used by birds than resources resembling natural waters (puddles, ponds, fountains). This novel finding may have particular importance for avian conservation planning, including appropriate behaviour for nature lovers (providing water sources and reducing stress to birds due to predation risk). Finally, we assessed potential threats to bathing and drinking birds, such as moving cars, risk of drowning, and the presence of predators. Any kind of surface water is currently beneficial for wild birds inhabiting human modified landscapes. During heatwaves and droughts access to water can be crucial for many birds. Unfortunately, such extreme events are predicted to become more frequent and more severe under climate change. Therefore, we would encourage further research in the use by birds of free-standing water, similar to the many studies of birdfeeders in winter, and to consider the maintenance of diverse sources of accessible water in environmental management.
Lightweight, high-efficiency and low reflection electromagnetic interference (EMI) shielding polymer composites are greatly desired for addressing the challenge of ever-increasing electromagnetic pollution. Lightweight layered foam/film PVDF nanocomposites with efficient EMI shielding effectiveness and ultralow reflection power were fabricated by physical foaming. The unique layered foam/film structure was composed of PVDF/SiCnw/MXene (Ti 3 C 2 T x ) composite foam as absorption layer and highly conductive PVDF/MWCNT/GnPs composite film as a reflection layer. The foam layer with numerous heterogeneous interfaces developed between the SiC nanowires (SiCnw) and 2D MXene nanosheets imparted superior EM wave attenuation capability. Furthermore, the microcellular structure effectively tuned the impedance matching and prolonged the wave propagating path by internal scattering and multiple reflections. Meanwhile, the highly conductive PVDF/MWCNT/GnPs composite (~ 220 S m ⁻¹ ) exhibited superior reflectivity (R) of 0.95. The tailored structure in the layered foam/film PVDF nanocomposite exhibited an EMI SE of 32.6 dB and a low reflection bandwidth of 4 GHz (R < 0.1) over the Ku-band (12.4 − 18.0 GHz) at a thickness of 1.95 mm. A peak SE R of 3.1 × 10 –4 dB was obtained which corresponds to only 0.0022% reflection efficiency. In consequence, this study introduces a feasible approach to develop lightweight, high-efficiency EMI shielding materials with ultralow reflection for emerging applications.
We present the magnetic, structural and ⁵⁷Fe Mossbauer characterization of soils collected from an ancient mercury contaminated city named Huancavelica in Peru. The characterization results indicate that silicates and carbonates are the main mineralogical constituents in the samples. In addition, ⁵⁷Fe Mössbauer spectra at room temperature reveal, the presence of two components: a magnetic component related to magnetic Fe-oxides (magnetite, hematite, goethite) and a high non-magnetic component related to Fe⁺³ in high spin configuration and tetrahedral coordination in silicates. The magnetization measurements present screening of paramagnetic, ferromagnetic and antiferromagnetic signals, typical from soils containing different silicates and iron minerals. Remarkably the Verwey and Morin transitions corresponding to magnetite and hematite, respectively, are screened by the paramagnetic signal corresponding to the major silicate components in the samples. Overall, the soils are mainly composed of crystalline and amorphous silicates, calcites and iron bearing which are typical from Andean soils.
The Large Hadron Collider beauty (LHCb) experiment at CERN is undergoing an upgrade in preparation for the Run 3 data collection period at the Large Hadron Collider (LHC). As part of this upgrade, the trigger is moving to a full software implementation operating at the LHC bunch crossing rate. We present an evaluation of a CPU-based and a GPU-based implementation of the first stage of the high-level trigger. After a detailed comparison, both options are found to be viable. This document summarizes the performance and implementation details of these options, the outcome of which has led to the choice of the GPU-based implementation as the baseline.
Background Genome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear. Methods Among 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes. Results Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate < 5%), most commonly ER and grade, followed by PR and HER2. Models for intrinsic-like subtypes found nearly all of these variants (83 of 85) associated at p < 0.05 with risk for at least one luminal-like subtype, and approximately half (41 of 85) of the variants were associated with risk of at least one non-luminal subtype, including 32 variants associated with triple-negative (TN) disease. Ten variants were associated with risk of all subtypes in different magnitude. Five variants were associated with risk of luminal A-like and TN subtypes in opposite directions. Conclusion This report demonstrates a high level of complexity in the etiology heterogeneity of breast cancer susceptibility variants and can inform investigations of subtype-specific risk prediction.
Background Disease-specific patient-reported outcome measures (PROMs) are fundamental to understanding the impact on, and expectations of, patients with genetic disorders, and can facilitate constructive and educated conversations about treatments and outcomes. However, generic PROMs may fail to capture disease-specific concerns. Here we report the development and validation of a Gaucher disease (GD)-specific PROM for patients with type 1 Gaucher disease (GD1) a lysosomal storage disorder characterized by hepatosplenomegaly, thrombocytopenia, anemia, bruising, bone disease, and fatigue. Results and discussion The questionnaire was initially developed with input from 85 patients or parents of patients with GD1 or GD3 in Israel. Owing to few participating patients with GD3, content validity was assessed for patients with GD1 only. Content validity of the revised questionnaire was assessed in 33 patients in the US, France, and Israel according to US Food and Drug Administration standards, with input from a panel of six GD experts and one patient advocate representative. Concept elicitation interviews explored patient experience of symptoms and treatments, and a cognitive debriefing exercise explored patients’ understanding and relevance of instructions, items, response scales, and recall period. Two versions of the questionnaire were subsequently developed: a 24-item version for routine monitoring in clinical practice (rmGD1-PROM), and a 17-item version for use in clinical trials (ctGD1-PROM). Psychometric validation of the ctGD1-PROM was assessed in 46 adult patients with GD1 and re-administered two weeks later to examine test–retest reliability. Findings from the psychometric validation study revealed excellent internal consistency and strong evidence of convergent validity of the ctGD1-PROM based on correlations with the 36-item Short Form Health Survey. Most items were found to show moderate, good, or excellent test–retest reliability. Conclusions Development of the ctGD1-PROM represents an important step forward for researchers measuring the impact of GD and its respective treatment.
The scalable production of two-dimensional (2D) materials is needed to accelerate their adoption to industry. In this work, we present a low-cost in-line and enclosed process of exfoliation based on high-shear mixing to create aqueous dispersions of few-layer graphene, on a large scale with a Y w ~ 100% yield by weight and throughput of ϕ ~ 8.3 g h ⁻¹ . The in-line process minimises basal plane defects compared to traditional beaker-based shear mixing which we attribute to a reduced Reynolds number, Re ~ 10 ⁵ . We demonstrate highly conductive graphene material with conductivities as high as σ ∼ 1.5 × 10 4 S m ⁻¹ leading to sheet-resistances as low as R s ∼ 2.6 Ω □ ⁻¹ ( t ∼ 25 μm). The process is ideal for formulating non-toxic, biocompatible and highly concentrated ( c ∼ 100 mg ml ⁻¹ ) inks. We utilise the graphene inks for inkjet printable conductive interconnects and lithium-ion battery anode composites that demonstrate a low-rate lithium storage capability of 370 mAh g ⁻¹ , close to the theoretical capacity of graphite. Finally, we demonstrate the biocompatibility of the graphene inks with human colon cells and human umbilical vein endothelial cells at high c ∼ 1 mg ml ⁻¹ facilitating a route for the use of the graphene inks in applications that require biocompatibility at high c such as electronic textiles.
The primary process in an electrical arc furnace (EAF) during industrial steelmaking results in tons of black slags which cause pollution to the environment. In this work, the iron oxides of black slags generated in the EAF from the SIDERPERU plant, Peru was reduced via the carbothermal reaction. The reduction of the black slag to α-Fe is demonstrated by X-ray diffraction, Mӧssbauer spectroscopy and magnetometry. However, phases with calcium and silicon persist in the sample after the carbothermal process. The thermodynamic calculations of the most probable reactions sequence were performed to understand the reduction process. The magnetometry measurements confirm the presence of ferromagnetic domains, supporting the success of the reduction of the black slag to α-Fe. The reduced black slags were recycled into a HRB335 steel rod by consolidation and extrusion processes and inspected by X-ray fluorescence.
Background Clinical endpoints for upcoming therapeutic trials in frontotemporal dementia (FTD) are increasingly urgent. Cognitive composite scores are often used as endpoints but are lacking in genetic FTD. We aimed to create cognitive composite scores for genetic frontotemporal dementia (FTD) as well as recommendations for recruitment and duration in clinical trial design. Methods A standardized neuropsychological test battery covering six cognitive domains was completed by 69 C9orf72 , 41 GRN , and 28 MAPT mutation carriers with CDR® plus NACC-FTLD ≥ 0.5 and 275 controls. Logistic regression was used to identify the combination of tests that distinguished best between each mutation carrier group and controls. The composite scores were calculated from the weighted averages of test scores in the models based on the regression coefficients. Sample size estimates were calculated for individual cognitive tests and composites in a theoretical trial aimed at preventing progression from a prodromal stage (CDR® plus NACC-FTLD 0.5) to a fully symptomatic stage (CDR® plus NACC-FTLD ≥ 1). Time-to-event analysis was performed to determine how quickly mutation carriers progressed from CDR® plus NACC-FTLD = 0.5 to ≥ 1 (and therefore how long a trial would need to be). Results The results from the logistic regression analyses resulted in different composite scores for each mutation carrier group (i.e. C9orf72 , GRN , and MAPT ). The estimated sample size to detect a treatment effect was lower for composite scores than for most individual tests. A Kaplan-Meier curve showed that after 3 years, ~ 50% of individuals had converted from CDR® plus NACC-FTLD 0.5 to ≥ 1, which means that the estimated effect size needs to be halved in sample size calculations as only half of the mutation carriers would be expected to progress from CDR® plus NACC FTLD 0.5 to ≥ 1 without treatment over that time period. Discussion We created gene-specific cognitive composite scores for C9orf72 , GRN , and MAPT mutation carriers, which resulted in substantially lower estimated sample sizes to detect a treatment effect than the individual cognitive tests. The GENFI-Cog composites have potential as cognitive endpoints for upcoming clinical trials. The results from this study provide recommendations for estimating sample size and trial duration.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.
27,536 members
Andreas Bender
  • Department of Chemistry
Yarjan Abdul Samad
  • Cambridge Graphene Centre
Chih-Chun Chen
  • Department of Engineering
Philippa Fawcett Dr, CB3 0AS, Cambridge, United Kingdom