Two-Locus Likelihoods under Variable Population Size and Fine-Scale Recombination Rate Estimation

Two-locus sampling probabilities have played a central role in devising an efficient composite likelihood method for estimating fine-scale recombination rates. Due to mathematical and computational challenges, these sampling probabilities are typically computed under the unrealistic assumption of a constant population size, and simulation studies have shown that resulting recombination rate estimates can be severely biased in certain cases of historical population size changes. To alleviate this problem, we develop here new methods to compute the sampling probability for variable population size functions that are piecewise constant. Our main theoretical result, implemented in a new software package called LDpop, is a novel formula for the sampling probability that can be evaluated by numerically exponentiating a large but sparse matrix. This formula can handle moderate sample sizes ($n \leq 50$) and demographic size histories with a large number of epochs ($\mathcal{D} \geq 64$). In addition, LDpop implements an approximate formula for the sampling probability that is reasonably accurate and scales to hundreds in sample size ($n \geq 256$). Finally, LDpop includes an importance sampler for the posterior distribution of two-locus genealogies, based on a new result for the optimal proposal distribution in the variable-size setting. Using our methods, we study how a sharp population bottleneck followed by rapid growth affects the correlation between partially linked sites. Then, through an extensive simulation study, we show that accounting for population size changes under such a demographic model leads to substantial improvements in fine-scale recombination rate estimation. LDpop is freely available for download at https://github.com/popgenmethods/ldpopComment: 32 pages, 13 figure

Applications of Secure Multiparty Computation

We generate and gather a lot of data about ourselves and others, some of it highly confidential. The collection, storage and use of this data is strictly regulated by laws, but restricting the use of data often limits the benefits which could be obtained from its analysis. Secure multi-party computation (SMC), a cryptographic technology, makes it possible to execute specific programs on confidential data while ensuring that no other sensitive information from the data is leaked. SMC has been the subject of academic study for more than 30 years, but first attempts to use it for actual computations in the early 2000s – although theoretically efficient – were initially not practicable. However, improvements in the situation have made possible the secure solving of even relatively large computational tasks. This book describes how many different computational tasks can be solved securely, yet efficiently. It describes how protocols can be combined to larger applications, and how the security-efficiency trade-offs of different components of an SMC application should be chosen. Many of the results described in this book were achieved as part of the project Usable and Efficient Secure Multi-party Computation (UaESMC), which was funded by the European Commission. The book will be of interest to all those whose work involves the secure analysis of confidential data

Development of a new immersive virtual reality (VR) headset-based dexterity training for patients with multiple sclerosis: Clinical and technical aspects.

BACKGROUND Impaired manual dexterity is frequent and disabling in patients with multiple sclerosis (MS), affecting activities of daily living and quality of life. OBJECTIVE To develop a new immersive virtual-reality (VR) headset-based dexterity training to improve impaired manual dexterity in persons with MS (pwMS) while being feasible and usable in a home-based setting. METHODS The training intervention was tailored to the specific group of pwMS by implementing a simple and intuitive application with regard to hardware and software. To be efficacious, the training intervention covers the main functions of the hands and arm relevant for use in everyday life. RESULTS Taking clinical, feasibility, usability as well as technical aspects with regard to hardware and software into account, six different training exercises using hand tracking technology were developed on the Meta quest 2 using Unity. CONCLUSION We report the developmental process of a new immersive virtual VR headset-based dexterity training for pwMS implementing clinical and technical aspects. Good feasibility, usability, and patient satisfaction was already shown in a feasibility study qualifying this training intervention for further efficacy trials

Cell contraction induces long-ranged stress stiffening in the extracellular matrix

Animal cells in tissues are supported by biopolymer matrices, which typically exhibit highly nonlinear mechanical properties. While the linear elasticity of the matrix can significantly impact cell mechanics and functionality, it remains largely unknown how cells, in turn, affect the nonlinear mechanics of their surrounding matrix. Here we show that living contractile cells are able to generate a massive stiffness gradient in three distinct 3D extracellular matrix model systems: collagen, fibrin, and Matrigel. We decipher this remarkable behavior by introducing Nonlinear Stress Inference Microscopy (NSIM), a novel technique to infer stress fields in a 3D matrix from nonlinear microrheology measurement with optical tweezers. Using NSIM and simulations, we reveal a long-ranged propagation of cell-generated stresses resulting from local filament buckling. This slow decay of stress gives rise to the large spatial extent of the observed cell-induced matrix stiffness gradient, which could form a mechanism for mechanical communication between cells

Open areas in a landscape enhance pollen-mediated gene flow of a tree species: evidence from northern Switzerland

Habitat fragmentation often has negative consequences for genetic diversity, and thereby for the viability of populations. However, these negative consequences might be counteracted by gene flow as the latter provides functional connectivity between apparently isolated habitat fragments. Gene flow is itself influenced by landscape structure and composition, and it is therefore important to understand the relationship between gene flow and landscape structure and composition. We used linear LAD regression models to investigate the relationship between contemporary gene flow by pollen in the rare, insect-pollinated forest tree Sorbus domestica and several landscape features. None of the landscape components—which included closed forest, deep valleys, open land and settlements—proved to be an impermeable barrier to gene flow by pollen. We found evidence that settlements, large open areas, and a pronounced topography increased long-distance gene flow in the landscape as compared to a random model including all possible gene flow trajectories. These results are encouraging from a conservation view, as gene flow in species pollinated by generalist insects seems to provide functional connectivity and may help to maintain genetic diversity in rare plant species in fragmented landscape

Mathematical and physical approaches to infer absolute zenith wet delays from double differential interferometric observations using ERA5 atmospheric reanalysis

Atmospheric water vapor (WV) is one of the driving constituents of the atmosphere. The modelling and forecasting of WV and derived quantities like precipitable water is reliable on regional scales but challenging on small scales because of its high spatial and temporal variation. Interferometric synthetic aperture radar (InSAR) can be exploited to retrieve integrated atmospheric water vapor (IWV) from path delay observations along the radar line of sight. InSAR-derived IWV maps feature a very high spatial resolution but the double-differential interferometric observations only provide changes of IWV between acquisition times and with respect to a certain spatial reference. In this study we present a method to derive the absolute IWV by combining ERA5 numerical weather model data with differential path delay observations from InSAR time series. We propose different functional approaches to merge the regional trend of WV from ERA5 with the high resolution IWV signal from InSAR. We apply this to a Sentinel-1 Persistent Scatterer InSAR time series in the Upper Rhine Graben and validate against IWV observations at GNSS stations of the Upper Rhine Graben Network

Feasibility and usability of a new home-based immersive virtual reality headset-based dexterity training in multiple sclerosis.

BACKGROUND Impaired manual dexterity is frequent and disabling in patients with multiple sclerosis (MS), affecting activities of daily living and quality of life. OBJECTIVE The aim of this study was to evaluate the feasibility, usability and patient engagement/satisfaction of a home-based immersive virtual reality (VR) headset-based dexterity training in persons with multiple sclerosis (pwMS). In addition, preliminary efficacy data on the impact of this new training on manual dexterity were collected. METHODS Single arm prospective study. After a waiting period of two weeks, pwMS performed a specifically developed home-based VR headset-based dexterity training using the Oculus quest 2 for two weeks with five training sessions/week, each session for approximately 20 minutes. Primary endpoints were feasibility (measured by the adherence rate), usability (System Usability Scale, SUS) and patient engagement/satisfaction (Custom User Engagement Questionnaire, CUEQ). Secondary exploratory efficacy endpoints, measured before and after the waiting period as well as after the training intervention, were the Nine-hole-Peg-Test (9HPT), Coin rotation task (CRT), Handheld JAMAR dynamometer, Arm Function in Multiple Sclerosis Questionnaire (AMSQ) and the Multiple Sclerosis Impact Scale 29 (MSIS 29). RESULTS Eleven pwMS (mean age 49 ± 10.87 SD, mean EDSS 4.28 ± 1.48 SD) participated in the study. Feasibility (adherence rate: 81.8%), usability (median SUS score 94 (IQR = 78-96)) and patient engagement/satisfaction (median 8 on scale of 1-10) of the VR training was very high. In addition, the CRT for the dominant hand improved significantly after training (p = 0.03). CONCLUSIONS The good results on feasibility, usability, and patient engagement/satisfaction qualify this home-based immersive VR headset-based dexterity training approach for the use in home-based neurorehabilitation in pwMS. Improved fine motor skills for the dominant hand suggest preliminary efficacy, but this needs to be proven in a future randomized-controlled trials

Digital Deblurring of CMB Maps II: Asymmetric Point Spread Function

In this second paper in a series dedicated to developing efficient numerical techniques for the deblurring Cosmic Microwave Background (CMB) maps, we consider the case of asymmetric point spread functions (PSF). Although conceptually this problem is not different from the symmetric case, there are important differences from the computational point of view because it is no longer possible to use some of the efficient numerical techniques that work with symmetric PSFs. We present procedures that permit the use of efficient techniques even when this condition is not met. In particular, two methods are considered: a procedure based on a Kronecker approximation technique that can be implemented with the numerical methods used with symmetric PSFs but that has the limitation of requiring only mildly asymmetric PSFs. The second is a variant of the classic Tikhonov technique that works even with very asymmetric PSFs but that requires discarding the edges of the maps. We provide details for efficient implementations of the algorithms. Their performance is tested on simulated CMB maps.Comment: 9 pages, 13 Figure

Patient-tailored multimodal neurorehabilitation: The Lucerne model

Neurorehabilitation is a rapidly developing subspecialty of neurology due to medical advances and growing knowledge on functional recovery from brain injury such as plasticity and regeneration in the nervous system. Furthermore, progress in modern technologies facilitate new therapeutic concepts. Patient-tailored, flexible multimodal neurorehabilitation is essential in neurological diseases due to the diversity of symptoms. In addition, rehabilitative treatment should be realized from disease onset. To fulfill these goals, the neurocenter of the Cantonal Hospital Lucerne established an uninterrupted treatment chain from the emergency stage to the social and occupational reintegration, which is described in this article with a focus on stroke, Parkinson’s disease, and multiple sclerosis patients

Synthesis of polyisocyanurate prepolymer and the resulting flexible elastomers with tunable mechanical properties

Polyurethane (PU) is used in a wide range of applications due to its diverse chemical and physical properties. To meet the increasing demands on thermal and mechanical properties of PU materials, polyisocyanurates(PIRs) have been introduced in PU materials as crosslinkers and due to their high decomposition temperature. We prepared a liquid PIR prepolymer with high PIR content by co-trimerization of 4,4’-methylene diphenyl diisocyanate (4,4’-MDI) and mono-isocyanates. The mono-isocyanate was synthesizedvia reaction between a 4,4’-MDI and a 2-ethyl-1-hexanol. The PIR prepolymer obtained was further reacted with long chain polyols and chain extenders in both solvent and solvent-free conditions, leading to PIR elastomers that exhibited good thermal stability with high char formation, and improvedmechanical properties with much higher Young’s modulus. This work demonstrates that the liquid PIR prepolymer can potentially be used in various large-scale industrial applications