Variational Bayesian Methods for Inferring Spatial Statistics and Nonlinear Dynamics

This thesis discusses four novel statistical methods and approximate inference techniques for analyzing structured neural and molecular sequence data. The main contributions are new algorithms for approximate inference and learning in Bayesian latent variable models involving spatial statistics and nonlinear dynamics. First, we propose an amortized variational inference method to separate a set of overlapping signals into spatially localized source functions without knowledge of the original signals or the mixing process. In the second part of this dissertation, we discuss two approaches for uncovering nonlinear, smooth latent dynamics from sequential data. Both algorithms construct variational families on extensions of nonlinear state space models where the underlying systems are described by hidden stochastic differential equations. The first method proposes a structured approximate posterior describing spatially-dependent linear dynamics, as well as an algorithm that relies on the fixed-point iteration method to achieve convergence. The second method proposes a variational backward simulation technique from an unbiased estimate of the marginal likelihood defined through a subsampling process. In the final chapter, we develop connections between discrete and continuous variational sequential search for Bayesian phylogenetic inference. We propose a technique that uses sequential search to construct a variational objective defined on the composite space of non-clock phylogenetic trees. Each of these techniques are motivated by real problems within computational biology and applied to provide insights into the underlying structure of complex data

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Temporal Trends in Transcatheter Aortic Valve Replacement in France: FRANCE 2 to FRANCE TAVI

International audienceBackground - Transcatheter aortic valve replacement (TAVR) is standard therapy for patients with severe aortic stenosis who are at high surgical risk. However, national data regarding procedural characteristics and clinical outcomes over time are limited. Objectives - The aim of this study was to assess nationwide performance trends and clinical outcomes of TAVR during a 6-year period. Methods - TAVRs performed in 48 centers across France between January 2013 and December 2015 were prospectively included in the FRANCE TAVI (French Transcatheter Aortic Valve Implantation) registry. Findings were further compared with those reported from the FRANCE 2 (French Aortic National CoreValve and Edwards 2) registry, which captured all TAVRs performed from January 2010 to January 2012 across 34 centers. Results - A total of 12,804 patients from FRANCE TAVI and 4,165 patients from FRANCE 2 were included in this analysis. The median age of patients was 84.6 years, and 49.7% were men. FRANCE TAVI participants were older but at lower surgical risk (median logistic European System for Cardiac Operative Risk Evaluation [EuroSCORE]: 15.0% vs. 18.4%; p < 0.001). More than 80% of patients in FRANCE TAVI underwent transfemoral TAVR. Transesophageal echocardiography guidance decreased from 60.7% to 32.3% of cases, whereas more recent procedures were increasingly performed in hybrid operating rooms (15.8% vs. 35.7%). Rates of Valve Academic Research Consortium-defined device success increased from 95.3% in FRANCE 2 to 96.8% in FRANCE TAVI (p < 0.001). In-hospital and 30-day mortality rates were 4.4% and 5.4%, respectively, in FRANCE TAVI compared with 8.2% and 10.1%, respectively, in FRANCE 2 (p < 0.001 for both). Stroke and potentially life-threatening complications, such as annulus rupture or aortic dissection, remained stable over time, whereas rates of cardiac tamponade and pacemaker implantation significantly increased. Conclusions - The FRANCE TAVI registry provided reassuring data regarding trends in TAVR performance in an all-comers population on a national scale. Nonetheless, given that TAVR indications are likely to expand to patients at lower surgical risk, concerns remain regarding potentially life-threatening complications and pacemaker implantation. (Registry of Aortic Valve Bioprostheses Established by Catheter [FRANCE TAVI]; NCT01777828)

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P &lt; 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)

TRY plant trait database - enhanced coverage and open access

10.1111/gcb.14904GLOBAL CHANGE BIOLOGY261119-18

Search for a very light NMSSM Higgs boson produced in decays of the 125 GeV scalar boson and decaying into τ\tau leptons in pp collisions at s\sqrt s= 8 TeV

A search for a very light Higgs boson decaying into a pair of tau leptons is presented within the framework of the next-to-minimal supersymmetric standard model. This search is based on a data set corresponding to an integrated luminosity of 19.7 inverse-femtobarns of proton-proton collisions collected by the CMS experiment at a centre-of-mass energy of 8 TeV. The signal is defined by the production of either of the two lightest scalars, h[1] or h[2], via gluon-gluon fusion and subsequent decay into a pair of the lightest Higgs bosons, a[1] or h[1]. The h[1] or h[2] boson is identified with the observed state at a mass of 125 GeV. The analysis searches for decays of the a[1] (h[1]) states into pairs of tau leptons and covers a mass range for the a[1] (h[1]) boson of 4 to 8 GeV. The search reveals no significant excess in data above standard model background expectations, and an upper limit is set on the signal production cross section times branching fraction as a function of the a[1] (h[1]) boson mass. The 95\% confidence level limit ranges from 4.5 pb at m(a[1]) (m(h[1])) = 8 GeV to 10.3 pb at m(a[1]) (m(h[1])) = 5 GeV