In the wake of the pandemic of coronavirus disease 2019 (COVID-19), contact tracing has become a key element of strategies to control the spread of severe acute respiratory syndrome coronavirus-2 ...(SARS-CoV-2). Given the rapid and intense spread of SARS-CoV-2, digital contact tracing has emerged as a potential complementary tool to support containment and mitigation efforts. Early modelling studies highlighted the potential of digital contact tracing to break transmission chains, and Google and Apple subsequently developed the Exposure Notification (EN) framework, making it available to the vast majority of smartphones. A growing number of governments have launched or announced EN-based contact tracing apps, but their effectiveness remains unknown. Here, we report early findings of the digital contact tracing app deployment in Switzerland. We demonstrate proof-of-principle that digital contact tracing reaches exposed contacts, who then test positive for SARS-CoV-2. This indicates that digital contact tracing is an effective complementary tool for controlling the spread of SARS-CoV-2. Continued technical improvement and international compatibility can further increase the efficacy, particularly also across country borders.
As of 2009, anticoagulation with citrate was standard practice in continuous renal replacement therapy (CRRT) for critically ill patients at the University Medical Centre of Saarland, Germany. ...Partial hepatic metabolism of citrate means accumulation may occur during CRRT in critically ill patients with impaired liver function. The aim of this study was to evaluate the actual influence of hepatic function on citrate-associated complications during long-term CRRT.
In a retrospective study conducted between January 2009 and November 2012, all cases of dialysis therapy performed in the interdisciplinary surgical intensive care unit were analysed. Inclusion criteria were CRRT and regional anticoagulation with citrate, pronounced liver dysfunction, and pathologically reduced indocyanine green plasma disappearance rate (ICG-PDR).
A total of 1339 CRRTs were performed in 69 critically ill patients with liver failure. At admission, the mean Model for End-stage Liver Disease score was 19.2, and the mean ICG-PDR was 9.8%. Eight patients were treated with liver replacement therapy, and 30 underwent transplants. The mortality rate was 40%. The mean duration of dialysis was 19.4 days, and the circuit patency was 62.2 h. Accumulation of citrate was detected indirectly by total serum calcium/ionised serum calcium (tCa/iCa) ratio > 2.4. This was noted in 16 patients (23.2%). Dialysis had not to be discontinued for metabolic disorder or accumulation of citrate in any case. In 26% of cases, metabolic alkalosis occurred with pH > 7.5. Interestingly, no correlation between citrate accumulation and liver function parameters was detected. Moreover, most standard laboratory liver function parameters showed poor predictive capabilities for accumulation of citrate.
Our findings indicate that extra-hepatic metabolism of citrate seems to exist, avoiding in most cases citrate accumulation in critically ill patients despite impaired liver function. Because the citric acid cycle is oxygen-dependent, disturbed microcirculation would result in inadequate citrate metabolism. Raising the tCa/iCa ratio would therefore be an indicator of severity of illness and mortality rather than of liver failure. However, further studies are warranted for confirmation.
The human voltage-gated sodium channel Nav1.7 plays a crucial role in transmission of noxious stimuli. The inherited pain disorder erythromelalgia (IEM) has been linked to Nav1.7 gain-of-function ...mutations. Here we show that the IEM-associated Q875E mutation located on the pore module of Nav1.7 produces a large hyperpolarizing shift (−18 mV) in the voltage dependence of activation. Three-dimensional homology modeling indicates that the side chains of Gln-875 and the gating charge Arg-214 of the domain I voltage sensor are spatially close in the activated conformation of the channel. We verified this proximity by using an engineered disulfide bridge approach. The Q875E mutation introduces a negative charge that may modify the local electrical field experienced by the voltage sensor and, upon activation, interact directly via a salt bridge with the Arg-214 gating charge residue. Together these processes could promote transition to, and stabilization of, the domain I voltage sensor in the activated conformation and thus produce the observed gain of function. In support of this hypothesis, an increase in the extracellular concentration of Ca2+ or Mg2+ reverted the voltage dependence of activation of the IEM mutant to near WT values, suggesting a cation-mediated electrostatic screening of the proposed interaction between Q875E and Arg-214.
Background: Nav1.7 mutations are associated with pain syndromes including erythromelalgia.
Results: Disulfide locking experiments and three-dimensional modeling show close proximity of residues Gln-875 and the gating charge Arg-214.
Conclusion: The erythromelalgia mutation Q875E introduces a salt bridge that stabilizes the domain I voltage sensor in the activated position.
Significance: An inter-domain interaction is the structural basis for a novel mechanism underlying this pain disorder.
Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing that addresses the shortcomings of traditional anonymisation techniques. The promise is that ...synthetic data drawn from generative models preserves the statistical properties of the original dataset but, at the same time, provides perfect protection against privacy attacks. In this work, we present the first quantitative evaluation of the privacy gain of synthetic data publishing and compare it to that of previous anonymisation techniques. Our evaluation of a wide range of state-of-the-art generative models demonstrates that synthetic data either does not prevent inference attacks or does not retain data utility. In other words, we empirically show that synthetic data does not provide a better tradeoff between privacy and utility than traditional anonymisation techniques. Furthermore, in contrast to traditional anonymisation, the privacy-utility tradeoff of synthetic data publishing is hard to predict. Because it is impossible to predict what signals a synthetic dataset will preserve and what information will be lost, synthetic data leads to a highly variable privacy gain and unpredictable utility loss. In summary, we find that synthetic data is far from the holy grail of privacy-preserving data publishing.
The promise of least-privilege learning -- to find feature representations that are useful for a learning task but prevent inference of any sensitive information unrelated to this task -- is highly ...appealing. However, so far this concept has only been stated informally. It thus remains an open question whether and how we can achieve this goal. In this work, we provide the first formalisation of the least-privilege principle for machine learning and characterise its feasibility. We prove that there is a fundamental trade-off between a representation's utility for a given task and its leakage beyond the intended task: it is not possible to learn representations that have high utility for the intended task but, at the same time prevent inference of any attribute other than the task label itself. This trade-off holds under realistic assumptions on the data distribution and regardless of the technique used to learn the feature mappings that produce these representations. We empirically validate this result for a wide range of learning techniques, model architectures, and datasets.
In this document, we analyse the potential harms a large-scale deployment of the Luca system might cause to individuals, venues, and communities. The Luca system is a digital presence tracing system ...designed to provide health departments with the contact information necessary to alert individuals who have visited a location at the same time as a SARS-CoV-2-positive person. Multiple regional health departments in Germany have announced their plans to deploy the Luca system for the purpose of presence tracing. The system's developers suggest its use across various types of venues: from bars and restaurants to public and private events, such religious or political gatherings, weddings, and birthday parties. Recently, an extension to include schools and other educational facilities was discussed in public. Our analysis of the potential harms of the system is based on the publicly available Luca Security Concept which describes the system's security architecture and its planned protection mechanisms. The Security Concept furthermore provides a set of claims about the system's security and privacy properties. Besides an analysis of harms, our analysis includes a validation of these claims.
This document describes and analyzes a system for secure and privacy-preserving proximity tracing at large scale. This system, referred to as DP3T, provides a technological foundation to help slow ...the spread of SARS-CoV-2 by simplifying and accelerating the process of notifying people who might have been exposed to the virus so that they can take appropriate measures to break its transmission chain. The system aims to minimise privacy and security risks for individuals and communities and guarantee the highest level of data protection. The goal of our proximity tracing system is to determine who has been in close physical proximity to a COVID-19 positive person and thus exposed to the virus, without revealing the contact's identity or where the contact occurred. To achieve this goal, users run a smartphone app that continually broadcasts an ephemeral, pseudo-random ID representing the user's phone and also records the pseudo-random IDs observed from smartphones in close proximity. When a patient is diagnosed with COVID-19, she can upload pseudo-random IDs previously broadcast from her phone to a central server. Prior to the upload, all data remains exclusively on the user's phone. Other users' apps can use data from the server to locally estimate whether the device's owner was exposed to the virus through close-range physical proximity to a COVID-19 positive person who has uploaded their data. In case the app detects a high risk, it will inform the user.
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