Genesis, Pathways, and Terminations of Intense Global Water Vapor Transport in Association with Large-Scale Climate Patterns

The CONNected objECT (CONNECT) algorithm is applied to global Integrated Water Vapor Transport data from the NASA's Modern-Era Retrospective Analysis for Research and Applications – Version 2 reanalysis product for the period of 1980 to 2016. The algorithm generates life-cycle records in time and space evolving strong vapor transport events. We show five regions, located in the midlatitudes, where events typically exist (off the coast of the southeast United States, eastern China, eastern South America, off the southern tip of South Africa, and in the southeastern Pacific Ocean). Global statistics show distinct genesis and termination regions and global seasonal peak frequency during Northern Hemisphere late fall/winter and Southern Hemisphere winter. In addition, the event frequency and geographical location are shown to be modulated by the Arctic Oscillation, Pacific North American Pattern, and the quasi-biennial oscillation. Moreover, a positive linear trend in the annual number of objects is reported, increasing by 3.58 objects year-over-year

Kinematically Redundant Octahedral Motion Platform for Virtual Reality Simulations

We propose a novel design of a parallel manipulator of Stewart Gough type for virtual reality application of single individuals; i.e. an omni-directional treadmill is mounted on the motion platform in order to improve VR immersion by giving feedback to the human body. For this purpose we modify the well-known octahedral manipulator in a way that it has one degree of kinematical redundancy; namely an equiform reconfigurability of the base. The instantaneous kinematics and singularities of this mechanism are studied, where especially "unavoidable singularities" are characterized. These are poses of the motion platform, which can only be realized by singular configurations of the mechanism despite its kinematic redundancy.Comment: 13 pages, 6 figure

Spectral plots and the representation and interpretation of biological data

It is basic question in biology and other fields to identify the char- acteristic properties that on one hand are shared by structures from a particular realm, like gene regulation, protein-protein interaction or neu- ral networks or foodwebs, and that on the other hand distinguish them from other structures. We introduce and apply a general method, based on the spectrum of the normalized graph Laplacian, that yields repre- sentations, the spectral plots, that allow us to find and visualize such properties systematically. We present such visualizations for a wide range of biological networks and compare them with those for networks derived from theoretical schemes. The differences that we find are quite striking and suggest that the search for universal properties of biological networks should be complemented by an understanding of more specific features of biological organization principles at different scales.Comment: 15 pages, 7 figure

AI in patient flow: applications of artificial intelligence to improve patient flow in NHS acute mental health inpatient units

Introduction: Growing demand for mental health services, coupled with funding and resource limitations, creates an opportunity for novel technological solutions including artificial intelligence (AI). This study aims to identify issues in patient flow on mental health units and align them with potential AI solutions, ultimately devising a model for their integration at service level. Method: Following a narrative literature review and pilot interview, 20 semi-structured interviews were conducted with AI and mental health experts. Thematic analysis was then used to analyse and synthesise gathered data and construct an enhanced model. Results: Predictive variables for length-of-stay and readmission rate are not consistent in the literature. There are, however, common themes in patient flow issues. An analysis identified several potential areas for AI-enhanced patient flow. Firstly, AI could improve patient flow by streamlining administrative tasks and optimising allocation of resources. Secondly, real-time data analytics systems could support clinician decision-making in triage, discharge, diagnosis and treatment stages. Finally, longer-term, development of solutions such as digital phenotyping could help transform mental health care to a more preventative, personalised model. Conclusions: Recommendations were formulated for NHS trusts open to adopting AI patient flow enhancements. Although AI offers many promising use-cases, greater collaborative investment and infrastructure are needed to deliver clinically validated improvements. Concerns around data-use, regulation and transparency remain, and hospitals must continue to balance guidelines with stakeholder priorities. Further research is needed to connect existing case studies and develop a framework for their evaluation

Feller Processes: The Next Generation in Modeling. Brownian Motion, L\'evy Processes and Beyond

We present a simple construction method for Feller processes and a framework for the generation of sample paths of Feller processes. The construction is based on state space dependent mixing of L\'evy processes. Brownian Motion is one of the most frequently used continuous time Markov processes in applications. In recent years also L\'evy processes, of which Brownian Motion is a special case, have become increasingly popular. L\'evy processes are spatially homogeneous, but empirical data often suggest the use of spatially inhomogeneous processes. Thus it seems necessary to go to the next level of generalization: Feller processes. These include L\'evy processes and in particular Brownian motion as special cases but allow spatial inhomogeneities. Many properties of Feller processes are known, but proving the very existence is, in general, very technical. Moreover, an applicable framework for the generation of sample paths of a Feller process was missing. We explain, with practitioners in mind, how to overcome both of these obstacles. In particular our simulation technique allows to apply Monte Carlo methods to Feller processes.Comment: 22 pages, including 4 figures and 8 pages of source code for the generation of sample paths of Feller processe

Single-cell RNA-sequencing reveals a distinct population of proglucagon-expressing cells specific to the mouse upper small intestine

Objectives: To identify sub-populations of intestinal preproglucagon-expressing (PPG) cells producing Glucagon-like Peptide-1, and their associated expression profiles of sensory receptors, thereby enabling the discovery of therapeutic strategies that target these cell populations for the treatment of diabetes and obesity. Methods: We performed single cell RNA sequencing of PPG-cells purified by flow cytometry from the upper small intestine of 3 GLU-Venus mice. Cells from 2 mice were sequenced at low depth, and from the third mouse at high depth. High quality sequencing data from 234 PPG-cells were used to identify clusters by tSNE analysis. qPCR was performed to compare the longitudinal and crypt/villus locations of cluster-specific genes. Immunofluorescence and mass spectrometry were used to confirm protein expression. Results: PPG-cells formed 3 major clusters: a group with typical characteristics of classical L-cells, including high expression of Gcg and Pyy (comprising 51% of all PPG-cells); a cell type overlapping with Gip-expressing K-cells (14%); and a unique cluster expressing Tph1 and Pzp that was predominantly located in proximal small intestine villi and co-produced 5-HT (35%). Expression of G-protein coupled receptors differed between clusters, suggesting the cell types are differentially regulated, and would be differentially targetable. Conclusions: Our findings support the emerging concept that many enteroendocrine cell populations are highly overlapping, with individual cells producing a range of peptides previously assigned to distinct cell types. Different receptor expression profiles across the clusters highlight potential drug targets to increase gut hormone secretion for the treatment of diabetes and obesity.Research in the FR/FMG lab is funded by a Wellcome joint investigator award (106262/Z/14/Z and 106263/Z/14/Z) and a joint MRC programme within the Metabolic Diseases Unit (MRC_MC_UU_12012/3). Single cell collection and analysis was supported through MRC Clinical Research Infrastructure funds for the Cambridge Single Cell Analysis Clinical Core Facility. Work in the Göttgens laboratory is supported by grants from the Wellcome Trust, Bloodwise, Cancer Research UK, NIDDK and core support grants by the Wellcome Trust to the Wellcome Trust-MRC Cambridge Stem Cell Institute

The UK's Global Health Respiratory Network: Improving respiratory health of the world's poorest through research collaborations.

Respiratory disorders are responsible for considerable morbidity, health care utilisation, societal costs and approximately one in five deaths worldwide [1-4]. Yet, despite this substantial health and societal burden – which particularly affects the world’s poorest populations and as such is a major contributor to global health inequalities – respiratory disorders have historically not received the policy priority they warrant. For example, despite causing an estimated 1000 deaths per day, less than half of the world’s countries collect data on asthma prevalence (http://www.globalasthmareport.org/). This is true for both communicable and non-communicable respiratory disorders, many of which are either amenable to treatment or preventable

Mutations in SPG11, encoding spatacsin, are a major cause of spastic paraplegia with thin corpus callosum.

Autosomal recessive hereditary spastic paraplegia (ARHSP) with thin corpus callosum (TCC) is a common and clinically distinct form of familial spastic paraplegia that is linked to the SPG11 locus on chromosome 15 in most affected families. We analyzed 12 ARHSP-TCC families, refined the SPG11 candidate interval and identified ten mutations in a previously unidentified gene expressed ubiquitously in the nervous system but most prominently in the cerebellum, cerebral cortex, hippocampus and pineal gland. The mutations were either nonsense or insertions and deletions leading to a frameshift, suggesting a loss-of-function mechanism. The identification of the function of the gene will provide insight into the mechanisms leading to the degeneration of the corticospinal tract and other brain structures in this frequent form of ARHSP