Mesoscale Adjustments within the Planetary Boundary Layer in Tropical and Extratropical Environments

A series of three papers comprised the research completed for this dissertation study. Each contribution examined mesoscale processes that occurred within the planetary boundary layer in the context of the chosen avenue of research. The premise of paper one centered on the daytime growth of the convective mixed layer over the continental mid-latitudes for the application of smoke management from wildland fire. An evaluation of the most robust practical technique for mixed-layer height estimation was performed using numerical model simulations and space-based lidar retrievals. Results revealed that daytime mixed-layer growth corresponded with the excitation of the turbulent kinetic energy (TKE) and layer height was best determined where the dissipation of TKE occurred in the vertical. Papers two and three were completed as a two-part series where emphasis was placed on the boundary layer dynamics associated with the precursor environment wherein Hurricane Sandy (October 2012) developed. And although greater attention was paid to the localized mesoscale dynamics, evaluation of the larger-scale influence was also examined across the entire northern hemisphere weeks in advance. Results from two mesoscale model simulations, a control run and no-terrain experiment, show that the precursor environment is highly influential to its developmental fate. In the case of Sandy, the surrounding orography imposed constraints on the environmental mass field such that a low-level curved momentum channel was produced upstream of the incipient disturbance (on its southwestern side) wherein vorticity generation was maximized and wrapped into the vortex inflow region. The latter westerly momentum also converged with a secondary low-level southerly jet feature that emanated into the vortex inflow region. Model results were evaluated against a suite of satellite data including composite brightness imagery, scatterometer surface wind data, space-based lidar retrievals, and Best Track data (on storm track, mean sea level pressure, and maximum tangential wind speed) from the National Hurricane Center database

Quantifying Shape of Star-Like Objects Using Shape Curves and A New Compactness Measure

Shape is an important indicator of the physical and chemical behavior of natural and engineered particulate materials (e.g., sediment, sand, rock, volcanic ash). It directly or indirectly affects numerous microscopic and macroscopic geologic, environmental and engineering processes. Due to the complex, highly irregular shapes found in particulate materials, there is a perennial need for quantitative shape descriptions. We developed a new characterization method (shape curve analysis) and a new quantitative measure (compactness, not the topological mathematical definition) by applying a fundamental principle that the geometric anisotropy of an object is a unique signature of its internal spatial distribution of matter. We show that this method is applicable to “star-like” particles, a broad mathematical definition of shape fulfilled by most natural and engineered particulate materials. This new method and measure are designed to be mathematically intermediate between simple parameters like sphericity and full 3D shape descriptions. For a “star-like” object discretized as a polyhedron made of surface planar elements, each shape curve describes the distribution of elemental surface area or volume. Using several thousand regular and highly irregular 3-D shape representations, built from model or real particles, we demonstrate that shape curves accurately encode geometric anisotropy by mapping surface area and volume information onto a pair of dimensionless 2-D curves. Each shape curve produces an intrinsic property (length of shape curve) that is used to describe a new definition of compactness, a property shown to be independent of translation, rotation, and scale. Compactness exhibits unique values for distinct shapes and is insensitive to changes in measurement resolution and noise. With increasing ability to rapidly capture digital representations of highly irregular 3-D shapes, this work provides a new quantitative shape measure for direct comparison of shape across classes of particulate materials

Practical multimodal care for cancer cachexia

Purpose of reviewCancer cachexia is common and reduces function, treatment tolerability and quality of life. Given its multifaceted pathophysiology a multimodal approach to cachexia management is advocated for, but can be difficult to realise in practice. We use a case-based approach to highlight practical approaches to the multimodal management of cachexia for patients across the cancer trajectory.Recent findingsFour cases with lung cancer spanning surgical resection, radical chemoradiotherapy, palliative chemotherapy and no anticancer treatment are presented. We propose multimodal care approaches that incorporate nutritional support, exercise, and anti-inflammatory agents, on a background of personalized oncology care and family-centred education. Collectively, the cases reveal that multimodal care is part of everyone's remit, often focuses on supported self-management, and demands buy-in from the patient and their family. Once operationalized, multimodal care approaches can be tested pragmatically, including alongside emerging pharmacological cachexia treatments.SummaryWe demonstrate that multimodal care for cancer cachexia can be achieved using simple treatments and without a dedicated team of specialists. The sharing of advice between health professionals can help build collective confidence and expertise, moving towards a position in which every team member feels they can contribute towards multimodal care

Dystrophin glycoprotein complex dysfunction:a regulatory link between muscular dystrophy and cancer cachexia

SummaryCachexia contributes to nearly a third of all cancer deaths, yet the mechanisms underlying skeletal muscle wasting in this syndrome remain poorly defined. We report that tumor-induced alterations in the muscular dystrophy-associated dystrophin glycoprotein complex (DGC) represent a key early event in cachexia. Muscles from tumor-bearing mice exhibited membrane abnormalities accompanied by reduced levels of dystrophin and increased glycosylation on DGC proteins. Wasting was accentuated in tumor mdx mice lacking a DGC but spared in dystrophin transgenic mice that blocked induction of muscle E3 ubiquitin ligases. Furthermore, DGC deregulation correlated positively with cachexia in patients with gastrointestinal cancers. Based on these results, we propose that, similar to muscular dystrophy, DGC dysfunction plays a critical role in cancer-induced wasting

Somatic gene therapy for cancer. The utility of transferrinfection in generating ‘tumor vaccines’

The last few years have seen the development of a branch of somatic gene therapy which aims at strengthening the immune surveillance of the body, leading to eradication of disseminated cancer tumor cells and occult micrometastases after surgical removal of the primary tumor. Such a tumor vaccination protocol calls for cultivation of the primary tumor tissue and the insertion of one of three types of genes into the isolated cultured tumor cells followed by irradiation of the transfected or transduced cells to render them incapable of further proliferation. The cells so treated constitute the ‘tumor vaccine’. A review of the literature suggests that for mouse models, in the initial period after inoculation, rejection of the tumor cells is usually effected by non-T-cell immunity, whereas the long-term systemic immune response is based on cytotoxic T-cells. High expression of the gene inserted into the tumor cells may be critical for the success of the vaccination procedure. Examples are given which indicate that transferrinfection, a procedure to introduce genes by adenovirus-augmented receptor-mediated endocytosis, meets some important prerequisites for successful application of this type of gene therapy

Carcinomas assemble a filamentous CXCL12-keratin-19 coating that suppresses T cell-mediated immune attack.

Cancer immunotherapy frequently fails because most carcinomas have few T cells, suggesting that cancers can suppress T cell infiltration. Here, we show that cancer cells of human pancreatic ductal adenocarcinoma (PDA), colorectal cancer, and breast cancer are coated with transglutaminase-2 (TGM2)-dependent covalent CXCL12-keratin-19 (KRT19) heterodimers that are organized as filamentous networks. Since a dimeric form of CXCL12 suppresses the motility of human T cells, we determined whether this polymeric CXCL12-KRT19 coating mediated T cell exclusion. Mouse tumors containing control PDA cells exhibited the CXCL12-KRT19 coating, excluded T cells, and did not respond to treatment with anti-PD-1 antibody. Tumors containing PDA cells not expressing either KRT19 or TGM2 lacked the CXCL12-KRT19 coating, were infiltrated with activated CD8+ T cells, and growth was suppressed with anti-PD-1 antibody treatment. Thus, carcinomas assemble a CXCL12-KRT19 coating to evade cancer immune attack

Effectiveness of testing, contact tracing and isolation interventions among the general population on reducing transmission of SARS-CoV-2 : a systematic review

We conducted a systematic literature review of general population testing, contact tracing, case isolation and contact quarantine interventions to assess their effectiveness in reducing SARS-CoV-2 transmission, as implemented in real-world settings. We designed a broad search strategy and aimed to identify peer-reviewed studies of any design provided there was a quantitative measure of effectiveness on a transmission outcome. Studies that assessed the effect of testing or diagnosis on disease outcomes via treatment, but did not assess a transmission outcome, were not included. We focused on interventions implemented among the general population rather than in specific settings; these were from anywhere in the world and published any time after 1 January 2020 until the end of 2022. From 26 720 titles and abstracts, 1181 were reviewed as full text, and 25 met our inclusion criteria. These 25 studies included one randomized control trial (RCT) and the remaining 24 analysed empirical data and made some attempt to control for confounding. Studies included were categorized by the type of intervention: contact tracing (seven studies); specific testing strategies (12 studies); strategies for isolating cases/contacts (four studies); and ‘test, trace, isolate' (TTI) as a part of a package of interventions (two studies). None of the 25 studies were rated at low risk of bias and many were rated as serious risk of bias, particularly due to the likely presence of uncontrolled confounding factors, which was a major challenge in assessing the independent effects of TTI in observational studies. These confounding factors are to be expected from observational studies during an on-going pandemic, when the emphasis was on reducing the epidemic burden rather than trial design. Findings from these 25 studies suggested an important public health role for testing followed by isolation, especially where mass and serial testing was used to reduce transmission. Some of the most compelling analyses came from examining fine-grained within-country data on contact tracing; while broader studies which compared behaviour between countries also often found TTI led to reduced transmission and mortality, this was not universal. There was limited evidence for the benefit of isolation of cases/contacts away from the home environment. One study, an RCT, showed that daily testing of contacts could be a viable strategy to replace lengthy quarantine of contacts. Based on the scarcity of robust empirical evidence, we were not able to draw any firm quantitative conclusions about the quantitative impact of TTI interventions in different epidemic contexts. While the majority of studies found that testing, tracing and isolation reduced transmission, evidence for the scale of this impact is only available for specific scenarios and hence is not necessarily generalizable. Our review therefore emphasizes the need to conduct robust experimental studies that help inform the likely quantitative impact of different TTI interventions on transmission and their optimal design. Work is needed to support such studies in the context of future emerging epidemics, along with assessments of the cost-effectiveness of TTI interventions, which was beyond the scope of this review but will be critical to decision-making. This article is part of the theme issue ‘The effectiveness of non-pharmaceutical interventions on the COVID-19 pandemic: the evidence’

NASA's Earth Science Use of Commercially Availiable Remote Sensing Datasets: Cover Image

The cover image incorporates high resolution stereo pairs acquired from the DigitalGlobe(R) QuickBird sensor. It shows a digital elevation model of Meteor Crater, Arizona at approximately 1.3 meter point-spacing. Image analysts used the Leica Photogrammetry Suite to produce the DEM. The outside portion was computed from two QuickBird panchromatic scenes acquired October 2006, while an Optech laser scan dataset was used for the crater s interior elevations. The crater s terrain model and image drape were created in a NASA Constellation Program project focused on simulating lunar surface environments for prototyping and testing lunar surface mission analysis and planning tools. This work exemplifies NASA s Scientific Data Purchase legacy and commercial high resolution imagery applications, as scientists use commercial high resolution data to examine lunar analog Earth landscapes for advanced planning and trade studies for future lunar surface activities. Other applications include landscape dynamics related to volcanism, hydrologic events, climate change, and ice movement

Challenges for modelling interventions for future pandemics

Funding: This work was supported by the Isaac Newton Institute (EPSRC grant no. EP/R014604/1). MEK was supported by grants from The Netherlands Organisation for Health Research and Development (ZonMw), grant number 10430022010001, and grant number 91216062, and by the H2020 Project 101003480 (CORESMA). RNT was supported by the UKRI, grant number EP/V053507/1. GR was supported by Fundação para a Ciência e a Tecnologia (FCT) project reference 131_596787873. and by the VERDI project 101045989 funded by the European Union. LP and CO are funded by the Wellcome Trust and the Royal Society (grant 202562/Z/16/Z). LP is also supported by the UKRI through the JUNIPER modelling consortium (grant number MR/V038613/1) and by The Alan Turing Institute for Data Science and Artificial Intelligence. HBS is funded by the Wellcome Trust and Royal Society (202562/Z/16/Z), and the Alexander von Humboldt Foundation. DV had support from the National Council for Scientific and Technological Development of Brazil (CNPq - Refs. 441057/2020-9, 424141/2018-3, 309569/2019-2). FS is supported by the UKRI through the JUNIPER modelling consortium (grant number MR/V038613/1). EF is supported by UKRI (Medical Research Council)/Department of Health and Social Care (National Insitute of Health Research) MR/V028618/1. JPG's work was supported by funding from the UK Health Security Agency and the UK Department of Health and Social Care.Mathematical modelling and statistical inference provide a framework to evaluate different non-pharmaceutical and pharmaceutical interventions for the control of epidemics that has been widely used during the COVID-19 pandemic. In this paper, lessons learned from this and previous epidemics are used to highlight the challenges for future pandemic control. We consider the availability and use of data, as well as the need for correct parameterisation and calibration for different model frameworks. We discuss challenges that arise in describing and distinguishing between different interventions, within different modelling structures, and allowing both within and between host dynamics. We also highlight challenges in modelling the health economic and political aspects of interventions. Given the diversity of these challenges, a broad variety of interdisciplinary expertise is needed to address them, combining mathematical knowledge with biological and social insights, and including health economics and communication skills. Addressing these challenges for the future requires strong cross-disciplinary collaboration together with close communication between scientists and policy makers.Publisher PDFPeer reviewe