Incidence of Isolated Biliary Atresia during the COVID Lockdown in Europe: Results from a Collaborative Project by RARE-Liver

Background: Biliary atresia (BA) is a rare cholangiopathy where one of the proposed aetiological mechanisms is an infectious viral trigger. Coronavirus disease-19 (COVID) lockdown restrictions were implemented to reduce the transmission of infections. Strictness of lockdown varied across European countries. This study aimed to investigate if there was an association between strictness of lockdown and change in isolated BA (IBA) incidence in Europe. Methods: We approached European centres involved in the European Reference Network RARE-LIVER. We included IBA patients born between 2015 and June 2020. We calculated the number of IBA patients born per centre per month. The Stringency Index (SI) was used as lockdown strictness indicator. The association between percentage change of mean number of IBA patients born per month and the SI was assessed. Results: We included 412 IBA patients from thirteen different centres. The median number of patients per month did not change: 6 (1–15) pre-lockdown and 7 (6–9) during lockdown (p = 0.34). There was an inverse association between SI and percentage change in IBA (B = -0.73, p = 0.03). Median age at Kasai portoenterostomy (days) did not differ between time periods (51 (9–179) vs. 53 (19–126), p = 0.73). Conclusion: In this European study, a stricter COVID-lockdown was seemingly accompanied by a simultaneous larger decrease in the number of IBA patients born per month in the lockdown. Results should be interpreted with caution due to the assumptions and limitations of the analysis

Fast and Energy-Efficient State Checkpointing for Intermittent Computing

Intermittently powered embedded devices ensure forward progress of programs through state checkpointing in non-volatile memory. Checkpointing is, however, expensive in energy and adds to the execution times. To minimize this overhead, we present DICE, a system that renders differential checkpointing profitable on these devices. DICE is unique because it is a software-only technique and efficient because it only operates in volatile main memory to evaluate the differential. DICE may be integrated with reactive (Hibernus) or proactive (MementOS, HarvOS) checkpointing systems, and arbitrary code can be enabled with DICE using automatic code-instrumentation requiring no additional programmer effort. By reducing the cost of checkpoints, DICE cuts the peak energy demand of these devices, allowing operation with energy buffers that are one-eighth of the size originally required, thus leading to benefits such as smaller device footprints and faster recharging to operational voltage level. The impact on final performance is striking: with DICE, Hibernus requires one order of magnitude fewer checkpoints and one order of magnitude shorter time to complete a workload in real-world settings

Demystifying Energy Consumption Dynamics in Transiently powered Computers

Transiently powered computers (TPCs) form the foundation of the battery-less Internet of Things, using energy harvesting and small capacitors to power their operation. This kind of power supply is characterized by extreme variations in supply voltage, as capacitors charge when harvesting energy and discharge when computing. We experimentally find that these variations cause marked fluctuations in clock speed and power consumption. Such a deceptively minor observation is overlooked in existing literature. Systems are thus designed and parameterized in overly conservative ways, missing on a number of optimizations. We rather demonstrate that it is possible to accurately model and concretely capitalize on these fluctuations. We derive an energy model as a function of supply voltage and prove its use in two settings. First, we develop EPIC, a compile-time energy analysis tool. We use it to substitute for the constant power assumption in existing analysis techniques, giving programmers accurate information on worst-case energy consumption of programs. When using EPIC with existing TPC system support, run-time energy efficiency drastically improves, eventually leading up to a 350% speedup in the time to complete a fixed workload. Further, when using EPIC with existing debugging tools, it avoids unnecessary program changes that hurt energy efficiency. Next, we extend the MSPsim emulator and explore its use in parameterizing a different TPC system support. The improvements in energy efficiency yield up to more than 1000% time speedup to complete a fixed workload

Inhaled Argon Impedes Hepatic Regeneration after Ischemia/Reperfusion Injury in Rats

Organoprotective effects of noble gases are subject of current research. One important field of interest is the effect of noble gases on hepatic regenerative capacity. For the noble gas argon, promising studies demonstrated remarkable experimental effects in neuronal and renal cells. The aim of this study was to investigate the effects of argon on the regenerative capacity of the liver after ischemia/reperfusion injury (IRI). Male, Sprague-Dawley rats underwent hepatic IRI by clamping of the hepatic artery. Expression of hepatoproliferative genes (HGF, IL-1β, IL-6, TNF), cell cycle markers (BrdU, TUNEL, Ki-67), and liver enzymes (ALT, AST, Bilirubin, LDH) were assessed 3, 36, and 96 h after IRI. Expression of IL-1β and IL-6 was significantly higher after argon inhalation after 36 h (IL-1β 5.0 vs. 8.7 fold, p = 0.001; IL-6 9.6 vs. 19.1 fold, p = 0.05). Ki-67 was higher in the control group compared to the argon group after 36 h (214.0 vs. 38.7 positive cells/1000 hepatocytes, p = 0.045). Serum levels of AST and ALT did not differ significantly between groups. Our data indicate that argon inhalation has detrimental effects on liver regeneration after IRI as measured by elevated levels of the proinflammatory cytokines IL-1β and IL-6 after 36 h. In line with these results, Ki-67 is decreased in the argon group, indicating a negative effect on liver regeneration in argon inhalation