Autoimmune cytopenias in children: When to think of primary immunodeficiency?

Autoimmune cytopenias are defined by autoantibodies' immune destruction of one or more blood elements. Most often it is autoimmune hemolytic anemia or immune thrombocytopenia or both that define Evans syndrome. It may be secondary to infection or to underlying pathology such as systemic autoimmune disease or primary immunodeficiency, especially when it becomes chronic over several years. Primary Immunodeficiencies or inborn errors of immunity (IEI) are no longer defined solely by infections: autoimmunity is part of the clinical features of several of these diseases. It is dominated by autoimmune cytopenias, in particular, immune thrombocytopenia (ITP) and autoimmune hemolytic anaemia (AIHA). The challenges for the clinician are the situations where autoimmune cytopenias are chronic, recurrent and/or refractory to the various long-term therapeutic options. Most of these therapies are similar in action and generally consist of non-mediated immune suppression or modulation. In these situations, primary Immunodeficiencies must be diagnosed as soon as possible to allow the initiation of a targeted treatment and to avoid several ineffective therapeutic lines.

Diagnostic guidance for hereditary neutropenia in children: Narrative literature review.

In the era of genomics, orientation in the face of hereditary neutropenia still requires, first and foremost, a good clinical and cytological analysis. The thirty responsible genes now explain 60% of congenital neutropenia. These are rare since they are only found in 1‰ of all congenital neutropenia, estimated at 1% of the population. The clinical examination looks for phenotypes associated with syndromic hereditary neutropenia and cytology will guide this etiological research thanks to the data collected from blood count and bone marrow analysis. The objective of this narrative literature review is to provide an overview of the most recent literature regarding acquired and congenital chronic neutropenia and will provide a decision tree to guide towards aetiology. This will allow a better discussion with geneticists even if the genotype-phenotype correlation is not very strong.

RcdMathLib: An Open Source Software Library for Computing on Resource-Limited Devices.

We developped an open source library called RcdMathLib for solving multivariate linear and nonlinear systems. RcdMathLib supports on-the-fly computing on low-cost and resource-constrained devices, e.g., microcontrollers. The decentralized processing is a step towards ubiquitous computing enabling the implementation of Internet of Things (IoT) applications. RcdMathLib is modular- and layer-based, whereby different modules allow for algebraic operations such as vector and matrix operations or decompositions. RcdMathLib also comprises a utilities-module providing sorting and filtering algorithms as well as methods generating random variables. It enables solving linear and nonlinear equations based on efficient decomposition approaches such as the Singular Value Decomposition (SVD) algorithm. The open source library also provides optimization methods such as Gauss-Newton and Levenberg-Marquardt algorithms for solving problems of regression smoothing and curve fitting. Furthermore, a positioning module permits computing positions of IoT devices using algorithms for instance trilateration. This module also enables the optimization of the position by performing a method to reduce multipath errors on the mobile device. The library is implemented and tested on resource-limited IoT as well as on full-fledged operating systems. The open source software library is hosted on a GitLab repository.

Accurate 3D Positioning for a Mobile Platform in Non-Line-of-Sight Scenarios Based on IMU/Magnetometer Sensor Fusion.

In recent years, a variety of real-time applications benefit from services provided by localization systems due to the advent of sensing and communication technologies. Since the Global Navigation Satellite System (GNSS) enables localization only outside buildings, applications for indoor positioning and navigation use alternative technologies. Ultra Wide Band Signals (UWB), Wireless Local Area Network (WLAN), ultrasonic or infrared are common examples. However, these technologies suffer from fading and multipath effects caused by objects and materials in the building. In contrast, magnetic fields are able to pass through obstacles without significant propagation errors, i.e. in Non-Line of Sight Scenarios (NLoS). The aim of this work is to propose a novel indoor positioning system based on artificially generated magnetic fields in combination with Inertial Measurement Units (IMUs). In order to reach a better coverage, multiple coils are used as reference points. A basic algorithm for three-dimensional applications is demonstrated as well as evaluated in this article. The established system is then realized by a sensor fusion principle as well as a kinematic motion model on the basis of a Kalman filter. Furthermore, a pressure sensor is used in combination with an adaptive filtering method to reliably estimate the platform's altitude.

Platform Architecture for Decentralized Positioning Systems.

A platform architecture for positioning systems is essential for the realization of a flexible localization system, which interacts with other systems and supports various positioning technologies and algorithms. The decentralized processing of a position enables pushing the application-level knowledge into a mobile station and avoids the communication with a central unit such as a server or a base station. In addition, the calculation of the position on low-cost and resource-constrained devices presents a challenge due to the limited computing, storage capacity, as well as power supply. Therefore, we propose a platform architecture that enables the design of a system with the reusability of the components, extensibility (e.g., with other positioning technologies) and interoperability. Furthermore, the position is computed on a low-cost device such as a microcontroller, which simultaneously performs additional tasks such as data collecting or preprocessing based on an operating system. The platform architecture is designed, implemented and evaluated on the basis of two positioning systems: a field strength system and a time of arrival-based positioning system.

Towards a Decentralized Magnetic Indoor Positioning System.

Decentralized magnetic indoor localization is a sophisticated method for processing sampled magnetic data directly on a mobile station (MS), thereby decreasing or even avoiding the need for communication with the base station. In contrast to central-oriented positioning systems, which transmit raw data to a base station, decentralized indoor localization pushes application-level knowledge into the MS. A decentralized position solution has thus a strong feasibility to increase energy efficiency and to prolong the lifetime of the MS. In this article, we present a complete architecture and an implementation for a decentralized positioning system. Furthermore, we introduce a technique for the synchronization of the observed magnetic field on the MS with the artificially-generated magnetic field from the coils. Based on real-time clocks (RTCs) and a preemptive operating system, this method allows a stand-alone control of the coils and a proper assignment of the measured magnetic fields on the MS. A stand-alone control and synchronization of the coils and the MS have an exceptional potential to implement a positioning system without the need for wired or wireless communication and enable a deployment of applications for rescue scenarios, like localization of miners or firefighters.