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"Reid, John"
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Messy cities : why we can't plan everything
\"Can messiness make our cities more liveable, lively, and inclusive? Crowded streets, sidewalk vendors, jumbled architecture, constant clamour, graffitied walls, parks gone wild: are these signs of a poorly managed city or indicators of urban vitality? Messy Cities: Why We Can't Plan Everything argues that spontaneity and urban work-around are not liabilities but essential elements in all thriving cities. Forty essays by a range of writers from around the world illuminate the role of messy urbanism in enabling creativity, enterprise, and grassroots initiatives to flourish within dense modern cities. With pieces on guerrilla beaches, desire lines, urban interruptions, and the inner lives of unlovely buildings written by experts from all walks of life, Messy Cities makes the case for embracing disorder while not shying away from confronting its challenges.\"-- Provided by publisher.
BOOK
A potent broadly neutralizing human RSV antibody targets conserved site IV of the fusion glycoprotein
Respiratory syncytial virus (RSV) infection is the leading cause of hospitalization and infant mortality under six months of age worldwide; therefore, the prevention of RSV infection in all infants represents a significant unmet medical need. Here we report the isolation of a potent and broadly neutralizing RSV monoclonal antibody derived from a human memory B-cell. This antibody, RB1, is equipotent on RSV A and B subtypes, potently neutralizes a diverse panel of clinical isolates in vitro and demonstrates in vivo protection. It binds to a highly conserved epitope in antigenic site IV of the RSV fusion glycoprotein. RB1 is the parental antibody to MK-1654 which is currently in clinical development for the prevention of RSV infection in infants.
Respiratory syncytial virus (RSV) is a leading cause of infant hospitalization. Here, the authors isolate a human monoclonal antibody that binds to a highly conserved epitope on the RSV fusion protein, neutralizes RSV A and B subtypes equipotently and is protective in the cotton rat model.
Journal Article
السلوك المضاد للمجتمع عند الأطفال والمراهقين : تحليل خاص بالنمو ونموذج للتدخل
هذا الكتاب خلاصة دراسات استمرت ثلاثين عاما في مراكز بحوث متخصصة وجامعات كان من أبرزها مركز بحوث أوريجون توصل فيها المؤلفون إلى الأسباب النفسية للسلوك المضاد للمجتمع عند الأطفال والمراهقين والذي قد يتطور إلى العنف وارتكاب النشئ للجرائم وإدمان المخدرات وما قد يصحب هذا من فشل دراسي وشذوذ جنسي وتبدأ هذه الأسباب منذ الطفولة المبكرة وتمتد حتى نهاية المراهقة وبداية مرحلة الرشد.
Book
Clusternomics: Integrative context-dependent clustering for heterogeneous datasets
Integrative clustering is used to identify groups of samples by jointly analysing multiple datasets describing the same set of biological samples, such as gene expression, copy number, methylation etc. Most existing algorithms for integrative clustering assume that there is a shared consistent set of clusters across all datasets, and most of the data samples follow this structure. However in practice, the structure across heterogeneous datasets can be more varied, with clusters being joined in some datasets and separated in others. In this paper, we present a probabilistic clustering method to identify groups across datasets that do not share the same cluster structure. The proposed algorithm, Clusternomics, identifies groups of samples that share their global behaviour across heterogeneous datasets. The algorithm models clusters on the level of individual datasets, while also extracting global structure that arises from the local cluster assignments. Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. We evaluated the model both on simulated and on real-world datasets. The simulated data exemplifies datasets with varying degrees of common structure. In such a setting Clusternomics outperforms existing algorithms for integrative and consensus clustering. In a real-world application, we used the algorithm for cancer subtyping, identifying subtypes of cancer from heterogeneous datasets. We applied the algorithm to TCGA breast cancer dataset, integrating gene expression, miRNA expression, DNA methylation and proteomics. The algorithm extracted clinically meaningful clusters with significantly different survival probabilities. We also evaluated the algorithm on lung and kidney cancer TCGA datasets with high dimensionality, again showing clinically significant results and scalability of the algorithm.
Journal Article
Ethnic and minority group differences in engagement with COVID-19 vaccination programmes – at Pandemic Pace; when vaccine confidence in mass rollout meets local vaccine hesitancy
Israel, the UK, the USA, and some other wealthier countries lead in the implementation of COVID-19 vaccine mass vaccination programmes. Evidence from these countries indicates that their ethnic minorities could be as disproportionately disadvantaged in COVID-19 vaccines roll-out as they were affected by COVID-19-related serious illnesses. Their disadvantage is linked to their lower social status and fewer social goods compared with dominant population groups.
Albeit limited by methodology, early studies attribute lower uptake of COVID-19 amongst ethnic minorities to the wider determinants of vaccine uptake, hesitancy or lack of vaccine confidence, including lower levels of trust and greater concerns about vaccine safety. Early sentinel studies are needed in all early adopter countries.
One emerging theme among those of reproductive age in minority communities concerns a worry regarding COVID-19 vaccine’s potential adverse effect on fertility. Respected professional groups reassure this is not a credible rationale. Drug and vaccine regulators use understandable, cautious and conditional language in emergency licencing of new gene-based vaccines. Technical assessments on whether there is any potential genotoxicity or reproductive toxicity should be more emphatic.
From a public health perspective, sentinel studies should identify such community concerns and act early to produce convincing explanations and evidence. Local public health workforces need to be diverse, multiskilled, and able to engage well with minorities and vulnerable groups. The local Directors of Public Health in the UK are based in each local government area and have a remit and opportunity to stimulate speedy action to increase vaccine uptake.
During the rapid Pandemic Pace of the vaccines roll-out, extra efforts to minimise uptake variations are likely to achieve improvements in the next year or two. We expect variations will not disappear however, given that underlying inequalities persist in less inclusive social systems.
Journal Article
Consistent and reproducible cultures of large-scale 3D mammary epithelial structures using an accessible bioprinting platform
Background
Standard three-dimensional (3D)
in vitro
culture techniques, such as those used for mammary epithelial cells, rely on random distribution of cells within hydrogels. Although these systems offer advantages over traditional 2D models, limitations persist owing to the lack of control over cellular placement within the hydrogel. This results in experimental inconsistencies and random organoid morphology. Robust, high-throughput experimentation requires greater standardization of 3D epithelial culture techniques.
Methods
Here, we detail the use of a 3D bioprinting platform as an investigative tool to control the 3D formation of organoids through the “self-assembly” of human mammary epithelial cells. Experimental bioprinting procedures were optimized to enable the formation of controlled arrays of individual mammary organoids. We define the distance and cell number parameters necessary to print individual organoids that do not interact between print locations as well as those required to generate large contiguous organoids connected through multiple print locations.
Results
We demonstrate that as few as 10 cells can be used to form 3D mammary structures in a single print and that prints up to 500 μm apart can fuse to form single large structures. Using these fusion parameters, we demonstrate that both linear and non-linear (contiguous circles) can be generated with sizes of 3 mm in length/diameter. We confirm that cells from individual prints interact to form structures with a contiguous lumen. Finally, we demonstrate that organoids can be printed into human collagen hydrogels, allowing for all-human 3D culture systems.
Conclusions
Our platform is adaptable to different culturing protocols and is superior to traditional random 3D culture techniques in efficiency, reproducibility, and scalability. Importantly, owing to the low-cost accessibility and computer numerical control–driven platform of our 3D bioprinter, we have the ability to disseminate our experiments with absolute precision to interested laboratories.
Journal Article
A 3D bioprinter platform for mechanistic analysis of tumoroids and chimeric mammary organoids
The normal mammary microenvironment can suppress tumorigenesis and redirect cancer cells to adopt a normal mammary epithelial cell fate
in vivo
. Understanding of this phenomenon offers great promise for novel treatment and detection strategies in cancer, but current model systems make mechanistic insights into the process difficult. We have recently described a low-cost bioprinting platform designed to be accessible for basic cell biology laboratories. Here we report the use of this system for the study of tumorigenesis and microenvironmental redirection of breast cancer cells. We show our bioprinter significantly increases tumoroid formation in 3D collagen gels and allows for precise generation of tumoroid arrays. We also demonstrate that we can mimic published
in vivo
findings by co-printing cancer cells along with normal mammary epithelial cells to generate chimeric organoids. These chimeric organoids contain cancer cells that take part in normal luminal formation. Furthermore, we show for the first time that cancer cells within chimeric structures have a significant increase in 5-hydroxymethylcytosine levels as compared to bioprinted tumoroids. These results demonstrate the capacity of our 3D bioprinting platform to study tumorigenesis and microenvironmental control of breast cancer and highlight a novel mechanistic insight into the process of microenvironmental control of cancer.
Journal Article
Emissions and CO2 Concentration—An Evidence Based Approach
The relation between CO2 emissions and atmospheric CO2 concentration has traditionally been treated with more or less complex models with several boxes. Our approach is motivated by the question of how much CO2 must necessarily be absorbed by sinks. This is determined by accepted measurements and the global carbon budget. Observations lead to the model assumption that carbon sinks, similar to oceans or the biosphere, are linearly dependent on CO2 concentration on a decadal scale. In particular, this implies the falsifiable hypothesis that oceanic and biological CO2 buffers have not significantly changed in the past 70 years and are not saturated in the foreseeable future. A statistical model with two parameters is built from the global carbon budget and two testable assumptions. This model explains the relation between CO2 emission and historical CO2 concentration data very well. The model gives estimates of the natural emissions, the pre-industrial CO2 equilibrium concentration levels, the half-life time of an emission pulse, and the future CO2 concentration level from a given emission scenario. It is validated by an ex-post forecast of the last 20 years. The important result is that, with the stated polices emission scenario of the International Energy Agency (IEA), the future CO2 concentrations will not rise above 475 ppm. The model is compared with the carbon module of the Bern model, mapping their complex impulse response functions (IRFs) to a single time variant absorption parameter.
Journal Article
STEME: A Robust, Accurate Motif Finder for Large Data Sets
Motif finding is a difficult problem that has been studied for over 20 years. Some older popular motif finders are not suitable for analysis of the large data sets generated by next-generation sequencing. We recently published an efficient approximation (STEME) to the EM algorithm that is at the core of many motif finders such as MEME. This approximation allows the EM algorithm to be applied to large data sets. In this work we describe several efficient extensions to STEME that are based on the MEME algorithm. Together with the original STEME EM approximation, these extensions make STEME a fully-fledged motif finder with similar properties to MEME. We discuss the difficulty of objectively comparing motif finders. We show that STEME performs comparably to existing prominent discriminative motif finders, DREME and Trawler, on 13 sets of transcription factor binding data in mouse ES cells. We demonstrate the ability of STEME to find long degenerate motifs which these discriminative motif finders do not find. As part of our method, we extend an earlier method due to Nagarajan et al. for the efficient calculation of motif E-values. STEME's source code is available under an open source license and STEME is available via a web interface.
Journal Article