A unified model-based framework for doublet or multiplet detection in single-cell multiomics data.

Droplet-based single-cell sequencing techniques rely on the fundamental assumption that each droplet encapsulates a single cell, enabling individual cell omics profiling. However, the inevitable issue of multiplets, where two or more cells are encapsulated within a single droplet, can lead to spurious cell type annotations and obscure true biological findings. The issue of multiplets is exacerbated in single-cell multiomics settings, where integrating cross-modality information for clustering can inadvertently promote the aggregation of multiplet clusters and increase the risk of erroneous cell type annotations. Here, we propose a compound Poisson model-based framework for multiplet detection in single-cell multiomics data. Leveraging experimental cell hashing results as the ground truth for multiplet status, we conducted trimodal DOGMA-seq experiments and generated 17 benchmarking datasets from two tissues, involving a total of 280,123 droplets. We demonstrated that the proposed method is an essential tool for integrating cross-modality multiplet signals, effectively eliminating multiplet clusters in single-cell multiomics data-a task at which the benchmarked single-omics methods proved inadequate.

Comprehensive benchmarking of CITE-seq versus DOGMA-seq single cell multimodal omics.

The recently developed method TEA-seq and similar DOGMA-seq single cell trimodal omics assays provide unprecedented opportunities for understanding cell biology, but independent evaluation is lacking. We explore the utility of DOGMA-seq compared to the bimodal CITE-seq assay in activated and stimulated human peripheral blood T cells. We find that single cell trimodal omics measurements after digitonin (DIG) permeabilization were generally better than after an alternative "low-loss lysis" (LLL) permeabilization condition. Next, we find that DOGMA-seq with optimized DIG permeabilization and its ATAC library provides more information, although its mRNA and cell surface protein libraries have slightly inferior quality, compared to CITE-seq.

GMM-Demux: sample demultiplexing, multiplet detection, experiment planning, and novel cell-type verification in single cell sequencing.

Identifying and removing multiplets are essential to improving the scalability and the reliability of single cell RNA sequencing (scRNA-seq). Multiplets create artificial cell types in the dataset. We propose a Gaussian mixture model-based multiplet identification method, GMM-Demux. GMM-Demux accurately identifies and removes multiplets through sample barcoding, including cell hashing and MULTI-seq. GMM-Demux uses a droplet formation model to authenticate putative cell types discovered from a scRNA-seq dataset. We generate two in-house cell-hashing datasets and compared GMM-Demux against three state-of-the-art sample barcoding classifiers. We show that GMM-Demux is stable and highly accurate and recognizes 9 multiplet-induced fake cell types in a PBMC dataset.

Development of multi-functional streetscape green infrastructure using a performance index approach.

This paper presents a performance evaluation framework for streetscape vegetation. A performance index (PI) is conceived using the following seven traits, specific to the street environments - Pollution Flux Potential (PFP), Carbon Sequestration Potential (CSP), Thermal Comfort Potential (TCP), Noise Attenuation Potential (NAP), Biomass Energy Potential (BEP), Environmental Stress Tolerance (EST) and Crown Projection Factor (CPF). Its application is demonstrated through a case study using fifteen street vegetation species from the UK, utilising a combination of direct field measurements and inventoried literature data. Our results indicate greater preference to small-to-medium size trees and evergreen shrubs over larger trees for streetscaping. The proposed PI approach can be potentially applied two-fold: one, for evaluation of the performance of the existing street vegetation, facilitating the prospects for further improving them through management strategies and better species selection; two, for planning new streetscapes and multi-functional biomass as part of extending the green urban infrastructure.

National climate policies across Europe and their impacts on cities strategies.

Globally, efforts are underway to reduce anthropogenic greenhouse gas emissions and to adapt to climate change impacts at the local level. However, there is a poor understanding of the relationship between city strategies on climate change mitigation and adaptation and the relevant policies at national and European level. This paper describes a comparative study and evaluation of cross-national policy. It reports the findings of studying the climate change strategies or plans from 200 European cities from Austria, Belgium, Estonia, Finland, France, Germany, Ireland, Italy, Netherlands, Spain and the United Kingdom. The study highlights the shared responsibility of global, European, national, regional and city policies. An interpretation and illustration of the influences from international and national networks and policy makers in stimulating the development of local strategies and actions is proposed. It was found that there is no archetypical way of planning for climate change, and multiple interests and motivations are inevitable. Our research warrants the need for a multi-scale approach to climate policy in the future, mainly ensuring sufficient capacity and resource to enable local authorities to plan and respond to their specific climate change agenda for maximising the management potentials for translating environmental challenges into opportunities.

Mitigating and adapting to climate change: multi-functional and multi-scale assessment of green urban infrastructure.

In order to develop climate resilient urban areas and reduce emissions, several opportunities exist starting from conscious planning and design of green (and blue) spaces in these landscapes. Green urban infrastructure has been regarded as beneficial, e.g. by balancing water flows, providing thermal comfort. This article explores the existing evidence on the contribution of green spaces to climate change mitigation and adaptation services. We suggest a framework of ecosystem services for systematizing the evidence on the provision of bio-physical benefits (e.g. CO2 sequestration) as well as social and psychological benefits (e.g. improved health) that enable coping with (adaptation) or reducing the adverse effects (mitigation) of climate change. The multi-functional and multi-scale nature of green urban infrastructure complicates the categorization of services and benefits, since in reality the interactions between various benefits are manifold and appear on different scales. We will show the relevance of the benefits from green urban infrastructures on three spatial scales (i.e. city, neighborhood and site specific scales). We will further report on co-benefits and trade-offs between the various services indicating that a benefit could in turn be detrimental in relation to other functions. The manuscript identifies avenues for further research on the role of green urban infrastructure, in different types of cities, climates and social contexts. Our systematic understanding of the bio-physical and social processes defining various services allows targeting stressors that may hamper the provision of green urban infrastructure services in individual behavior as well as in wider planning and environmental management in urban areas.

The energy-water-food nexus: strategic analysis of technologies for transforming the urban metabolism.

Urban areas are considered net consumers of materials and energy, attracting these from the surrounding hinterland and other parts of the planet. The way these flows are transformed and returned to the environment by the city is important for addressing questions of sustainability and the effect of human behavior on the metabolism of the city. The present work explores these questions with the use of systems analysis, specifically in the form of a Multi-sectoral Systems Analysis (MSA), a tool for research and for supporting decision-making for policy and investment. The application of MSA is illustrated in the context of Greater London, with these three objectives: (a) estimating resource fluxes (nutrients, water and energy) entering, leaving and circulating within the city-watershed system; (b) revealing the synergies and antagonisms resulting from various combinations of water-sector innovations; and (c) estimating the economic benefits associated with implementing these technologies, from the point of view of production of fertilizer and energy, and the reduction of greenhouse gases. Results show that the selection of the best technological innovation depends on which resource is the focus for improvement. Urine separation can potentially recover 47% of the nitrogen in the food consumed in London, with revenue of $33 M per annum from fertilizer production. Collecting food waste in sewers together with growing algae in wastewater treatment plants could beneficially increase the amount of carbon release from renewable energy by 66%, with potential annual revenues of $58 M from fuel production.

Genomic analysis of immediate/early response to shear stress in human coronary artery endothelial cells.

The involvement of shear stress in the pathogenesis of vascular disease has motivated efforts to define the endothelial cell response to applied shear stress in vitro. A central question has been the mechanisms by which endothelial cells perceive and respond to changes in fluid flow. We have utilized cDNA microarrays to characterize the immediate/early genomic response to applied laminar shear stress (LSS) in primary cultures of human coronary artery endothelial cells (HCAECs). Cells were exposed, in a parallel plate flow chamber, to 0, 15, or 45 dyn/cm2 LSS for 1 h, and gene expression profiles were determined using human GEM1 cDNA microarrays. We find that a high proportion of LSS-responsive genes are transcription factors, and these are related by their involvement in growth arrest. These likely play a central role in the reprogramming of endothelial homeostasis following the switch from a static to a shear-stressed environment. LSS-responsive genes were also found to encode factors involved in vasoreactivity, signal transduction, antioxidants, cell cycle-associated genes, and markers of cytoskeletal function and dynamics.

Molecular anatomy of an intracranial aneurysm: coordinated expression of genes involved in wound healing and tissue remodeling.

BACKGROUND AND PURPOSE: Approximately 6% of human beings harbor an unruptured intracranial aneurysm. Each year in the United States, >30 000 people suffer a ruptured intracranial aneurysm, resulting in subarachnoid hemorrhage. Despite the high incidence and catastrophic consequences of a ruptured intracranial aneurysm and the fact that there is considerable evidence that predisposition to intracranial aneurysm has a strong genetic component, very little is understood with regard to the pathology and pathogenesis of this disease. METHODS: To begin characterizing the molecular pathology of intracranial aneurysm, we used a global gene expression analysis approach (SAGE-Lite) in combination with a novel data-mining approach to perform a high-resolution transcript analysis of a single intracranial aneurysm, obtained from a 3-year-old girl. RESULTS: SAGE-Lite provides a detailed molecular snapshot of a single intracranial aneurysm. These data suggest that, at least in this specific case, aneurysmal dilation results in a highly dynamic cellular environment in which extensive wound healing and tissue/extracellular matrix remodeling are taking place. Specifically, we observed significant overexpression of genes encoding extracellular matrix components (eg, COL3A1, COL1A1, COL1A2, COL6A1, COL6A2, elastin) and genes involved in extracellular matrix turnover (TIMP-3, OSF-2), cell adhesion and antiadhesion (SPARC, hevin), cytokinesis (PNUTL2), and cell migration (tetraspanin-5). CONCLUSIONS: Although these are preliminary data, representing analysis of only one individual, we present a unique first insight into the molecular basis of aneurysmal disease and define numerous candidate markers for future biochemical, physiological, and genetic studies of intracranial aneurysm. Products of these genes will be the focus of future studies in wider sample sets.