Managing extreme AI risks amid rapid progress.

Preparation requires technical research and development, as well as adaptive, proactive governance.

The effects of creatine supplementation on cognitive performance-a randomised controlled study.

BACKGROUND: Creatine is an organic compound that facilitates the recycling of energy-providing adenosine triphosphate (ATP) in muscle and brain tissue. It is a safe, well-studied supplement for strength training. Previous studies have shown that supplementation increases brain creatine levels, which might increase cognitive performance. The results of studies that have tested cognitive performance differ greatly, possibly due to different populations, supplementation regimens, and cognitive tasks. This is the largest study on the effect of creatine supplementation on cognitive performance to date. METHODS: Our trial was preregistered, cross-over, double-blind, placebo-controlled, and randomised, with daily supplementation of 5 g for 6 weeks each. We tested participants on Raven's Advanced Progressive Matrices (RAPM) and on the Backward Digit Span (BDS). In addition, we included eight exploratory cognitive tests. About half of our 123 participants were vegetarians and half were omnivores. RESULTS: Bayesian evidence supported a small beneficial effect of creatine. The creatine effect bordered significance for BDS (p = 0.064, η2P = 0.029) but not RAPM (p = 0.327, η2P = 0.008). There was no indication that creatine improved the performance of our exploratory cognitive tasks. Side effects were reported significantly more often for creatine than for placebo supplementation (p = 0.002, RR = 4.25). Vegetarians did not benefit more from creatine than omnivores. CONCLUSIONS: Our study, in combination with the literature, implies that creatine might have a small beneficial effect. Larger studies are needed to confirm or rule out this effect. Given the safety and broad availability of creatine, this is well worth investigating; a small effect could have large benefits when scaled over time and over many people. TRIAL REGISTRATION: The trial was prospectively registered (drks.de identifier: DRKS00017250, https://osf.io/xpwkc/ ).

Effectiveness assessment of non-pharmaceutical interventions: lessons learned from the COVID-19 pandemic.

Effectiveness of non-pharmaceutical interventions (NPIs), such as school closures and stay-at-home orders, during the COVID-19 pandemic has been assessed in many studies. Such assessments can inform public health policies and contribute to evidence-based choices of NPIs during subsequent waves or future epidemics. However, methodological issues and no standardised assessment practices have restricted the practical value of the existing evidence. Here, we present and discuss lessons learned from the COVID-19 pandemic and make recommendations for standardising and improving assessment, data collection, and modelling. These recommendations could contribute to reliable and policy-relevant assessments of the effectiveness of NPIs during future epidemics.

Mapping global dynamics of benchmark creation and saturation in artificial intelligence.

Benchmarks are crucial to measuring and steering progress in artificial intelligence (AI). However, recent studies raised concerns over the state of AI benchmarking, reporting issues such as benchmark overfitting, benchmark saturation and increasing centralization of benchmark dataset creation. To facilitate monitoring of the health of the AI benchmarking ecosystem, we introduce methodologies for creating condensed maps of the global dynamics of benchmark creation and saturation. We curate data for 3765 benchmarks covering the entire domains of computer vision and natural language processing, and show that a large fraction of benchmarks quickly trends towards near-saturation, that many benchmarks fail to find widespread utilization, and that benchmark performance gains for different AI tasks are prone to unforeseen bursts. We analyze attributes associated with benchmark popularity, and conclude that future benchmarks should emphasize versatility, breadth and real-world utility.

100,000 lumens to treat seasonal affective disorder: A proof of concept RCT of Bright, whole-ROom, All-Day (BROAD) light therapy.

BACKGROUND: Seasonal affective disorder (SAD) is common and debilitating. The standard of care includes light therapy provided by a light box; however, this treatment is restrictive and only moderately effective. Advances in LED technology enable lighting solutions that emit vastly more light than traditional light boxes. Here, we assess the feasibility of BROAD (Bright, whole-ROom, All-Day) light therapy and get a first estimate for its potential effectiveness. METHODS: Patients were randomly assigned to a treatment for 4 weeks; either a very brightly illuminated room in their home for at least 6 h per day (BROAD light therapy) or 30 min in front of a standard 10,000 lux SAD light box. Feasibility was assessed by monitoring recruitment, adherence, and side effects. SAD symptoms were measured at baseline and after 2 and 4 weeks, with the Hamilton Depression Rating Scale-Seasonal Affective Disorders 29-items, self-report version. RESULTS: All 62 patients who started treatment were available at 4-week follow-up and no significant adverse effects were reported. SAD symptoms of both groups improved similarly and considerably, in line with previous results. Exploratory analyses indicate that a higher illuminance (lux) is associated with a larger symptom improvement in the BROAD light therapy group. CONCLUSIONS: BROAD light therapy is feasible and seems similarly effective as the standard of care while not confining the participants to 30 min in front of a light box. In follow-up trials, BROAD light therapy could be modified for increased illuminance, which would likely improve its effectiveness.

Seasonal variation in SARS-CoV-2 transmission in temperate climates: A Bayesian modelling study in 143 European regions.

Although seasonal variation has a known influence on the transmission of several respiratory viral infections, its role in SARS-CoV-2 transmission remains unclear. While there is a sizable and growing literature on environmental drivers of COVID-19 transmission, recent reviews have highlighted conflicting and inconclusive findings. This indeterminacy partly owes to the fact that seasonal variation relates to viral transmission by a complicated web of causal pathways, including many interacting biological and behavioural factors. Since analyses of specific factors cannot determine the aggregate strength of seasonal forcing, we sidestep the challenge of disentangling various possible causal paths in favor of a holistic approach. We model seasonality as a sinusoidal variation in transmission and infer a single Bayesian estimate of the overall seasonal effect. By extending two state-of-the-art models of non-pharmaceutical intervention (NPI) effects and their datasets covering 143 regions in temperate Europe, we are able to adjust our estimates for the role of both NPIs and mobility patterns in reducing transmission. We find strong seasonal patterns, consistent with a reduction in the time-varying reproduction number R(t) (the expected number of new infections generated by an infectious individual at time t) of 42.1% (95% CI: 24.7%-53.4%) from the peak of winter to the peak of summer. These results imply that the seasonality of SARS-CoV-2 transmission is comparable in magnitude to the most effective individual NPIs but less than the combined effect of multiple interventions.

Mask wearing in community settings reduces SARS-CoV-2 transmission.

The effectiveness of mask wearing at controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been unclear. While masks are known to substantially reduce disease transmission in healthcare settings [D. K. Chu et al., Lancet 395, 1973­1987 (2020); J. Howard et al., Proc. Natl. Acad. Sci. U.S.A. 118, e2014564118 (2021); Y. Cheng et al., Science eabg6296 (2021)], studies in community settings report inconsistent results [H. M. Ollila et al., medRxiv (2020); J. Brainard et al., Eurosurveillance 25, 2000725 (2020); T. Jefferson et al., Cochrane Database Syst. Rev. 11, CD006207 (2020)]. Most such studies focus on how masks impact transmission, by analyzing how effective government mask mandates are. However, we find that widespread voluntary mask wearing, and other data limitations, make mandate effectiveness a poor proxy for mask-wearing effectiveness. We directly analyze the effect of mask wearing on SARS-CoV-2 transmission, drawing on several datasets covering 92 regions on six continents, including the largest survey of wearing behavior (n= 20 million) [F. Kreuter et al., https://gisumd.github.io/COVID-19-API-Documentation (2020)]. Using a Bayesian hierarchical model, we estimate the effect of mask wearing on transmission, by linking reported wearing levels to reported cases in each region, while adjusting for mobility and nonpharmaceutical interventions (NPIs), such as bans on large gatherings. Our estimates imply that the mean observed level of mask wearing corresponds to a 19% decrease in the reproduction number R. We also assess the robustness of our results in 60 tests spanning 20 sensitivity analyses. In light of these results, policy makers can effectively reduce transmission by intervening to increase mask wearing.

A dataset of non-pharmaceutical interventions on SARS-CoV-2 in Europe.

During the second half of 2020, many European governments responded to the resurging transmission of SARS-CoV-2 with wide-ranging non-pharmaceutical interventions (NPIs). These efforts were often highly targeted at the regional level and included fine-grained NPIs. This paper describes a new dataset designed for the accurate recording of NPIs in Europe's second wave to allow precise modelling of NPI effectiveness. The dataset includes interventions from 114 regions in 7 European countries during the period from the 1st August 2020 to the 9th January 2021. The paper includes NPI definitions tailored to the second wave following an exploratory data collection. Each entry has been extensively validated by semi-independent double entry, comparison with existing datasets, and, when necessary, discussion with local epidemiologists. The dataset has considerable potential for use in disentangling the effectiveness of NPIs and comparing the impact of interventions across different phases of the pandemic.

Prevalence and patterns of HIV drug resistance in patients with suspected virological failure in North-Western Tanzania.

BACKGROUND: More than 15 million people in sub-Saharan Africa receive ART. Treatment failure is common, but the role of HIV drug resistance in treatment failure is largely unknown because drug resistance testing is not routinely done. This study determined the prevalence and patterns of HIV drug resistance in patients with suspected virological failure. MATERIALS AND METHODS: A single high viral load of >1000 viral RNA copies/mL of plasma at any point during ART was considered as suspected virological failure. HIV-1 RNA was extracted from plasma samples of these patients using the QIAamp Viral RNA kit. The protease and part of the RT regions of the HIV pol gene were characterized. RESULTS: Viral load was determined in 317 patients; 64 (20.2%) had suspected virological failure. We successfully genotyped 56 samples; 48 (85.7%) had at least one major resistance-associated mutation (RAM). Common mutations in RT were M184V (75%), T215Y (41.1%), K103N (39.3%), M41L (32.1%), D67DN (30.3%), G190A (28.6%) and A98G (26.8%). No RAMs were detected in ART regimens based on a ritonavir-boosted PI. CONCLUSIONS: The Tanzanian national guidelines define 'virological failure' as two consecutive viral load measurement results, at 3 month intervals, above the WHO threshold (1000 copies/mL). Here, we show that a single viral load above the WHO threshold is associated with high rates of RAMs. This suggests that a single high viral load measurement could be used to predict virological failure and avoid delays in switching patients from first-line to higher genetic barrier second-line regimens.

All-cause versus cause-specific excess deaths for estimating influenza-associated mortality in Denmark, Spain, and the United States.

BACKGROUND: Seasonal influenza-associated excess mortality estimates can be timely and provide useful information on the severity of an epidemic. This methodology can be leveraged during an emergency response or pandemic. METHOD: For Denmark, Spain, and the United States, we estimated age-stratified excess mortality for (i) all-cause, (ii) respiratory and circulatory, (iii) circulatory, (iv) respiratory, and (v) pneumonia, and influenza causes of death for the 2015/2016 and 2016/2017 influenza seasons. We quantified differences between the countries and seasonal excess mortality estimates and the death categories. We used a time-series linear regression model accounting for time and seasonal trends using mortality data from 2010 through 2017. RESULTS: The respective periods of weekly excess mortality for all-cause and cause-specific deaths were similar in their chronological patterns. Seasonal all-cause excess mortality rates for the 2015/2016 and 2016/2017 influenza seasons were 4.7 (3.3-6.1) and 14.3 (13.0-15.6) per 100,000 population, for the United States; 20.3 (15.8-25.0) and 24.0 (19.3-28.7) per 100,000 population for Denmark; and 22.9 (18.9-26.9) and 52.9 (49.1-56.8) per 100,000 population for Spain. Seasonal respiratory and circulatory excess mortality estimates were two to three times lower than the all-cause estimates. DISCUSSION: We observed fewer influenza-associated deaths when we examined cause-specific death categories compared with all-cause deaths and observed the same trends in peaks in deaths with all death causes. Because all-cause deaths are more available, these models can be used to monitor virus activity in near real time. This approach may contribute to the development of timely mortality monitoring systems during public health emergencies.

Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe.

European governments use non-pharmaceutical interventions (NPIs) to control resurging waves of COVID-19. However, they only have outdated estimates for how effective individual NPIs were in the first wave. We estimate the effectiveness of 17 NPIs in Europe's second wave from subnational case and death data by introducing a flexible hierarchical Bayesian transmission model and collecting the largest dataset of NPI implementation dates across Europe. Business closures, educational institution closures, and gathering bans reduced transmission, but reduced it less than they did in the first wave. This difference is likely due to organisational safety measures and individual protective behaviours-such as distancing-which made various areas of public life safer and thereby reduced the effect of closing them. Specifically, we find smaller effects for closing educational institutions, suggesting that stringent safety measures made schools safer compared to the first wave. Second-wave estimates outperform previous estimates at predicting transmission in Europe's third wave.

Changing composition of SARS-CoV-2 lineages and rise of Delta variant in England.

BACKGROUND: Since its emergence in Autumn 2020, the SARS-CoV-2 Variant of Concern (VOC) B.1.1.7 (WHO label Alpha) rapidly became the dominant lineage across much of Europe. Simultaneously, several other VOCs were identified globally. Unlike B.1.1.7, some of these VOCs possess mutations thought to confer partial immune escape. Understanding when and how these additional VOCs pose a threat in settings where B.1.1.7 is currently dominant is vital. METHODS: We examine trends in the prevalence of non-B.1.1.7 lineages in London and other English regions using passive-case detection PCR data, cross-sectional community infection surveys, genomic surveillance, and wastewater monitoring. The study period spans from 31st January 2021 to 15th May 2021. FINDINGS: Across data sources, the percentage of non-B.1.1.7 variants has been increasing since late March 2021. This increase was initially driven by a variety of lineages with immune escape. From mid-April, B.1.617.2 (WHO label Delta) spread rapidly, becoming the dominant variant in England by late May. INTERPRETATION: The outcome of competition between variants depends on a wide range of factors such as intrinsic transmissibility, evasion of prior immunity, demographic specificities and interactions with non-pharmaceutical interventions. The presence and rise of non-B.1.1.7 variants in March likely was driven by importations and some community transmission. There was competition between non-B.1.17 variants which resulted in B.1.617.2 becoming dominant in April and May with considerable community transmission. Our results underscore that early detection of new variants requires a diverse array of data sources in community surveillance. Continued real-time information on the highly dynamic composition and trajectory of different SARS-CoV-2 lineages is essential to future control efforts. FUNDING: National Institute for Health Research, Medicines and Healthcare products Regulatory Agency, DeepMind, EPSRC, EA Funds programme, Open Philanthropy, Academy of Medical Sciences Bill,Melinda Gates Foundation, Imperial College Healthcare NHS Trust, The Novo Nordisk Foundation, MRC Centre for Global Infectious Disease Analysis, Community Jameel, Cancer Research UK, Imperial College COVID-19 Research Fund, Medical Research Council, Wellcome Sanger Institute.

Inferring the effectiveness of government interventions against COVID-19.

Governments are attempting to control the COVID-19 pandemic with nonpharmaceutical interventions (NPIs). However, the effectiveness of different NPIs at reducing transmission is poorly understood. We gathered chronological data on the implementation of NPIs for several European and non-European countries between January and the end of May 2020. We estimated the effectiveness of these NPIs, which range from limiting gathering sizes and closing businesses or educational institutions to stay-at-home orders. To do so, we used a Bayesian hierarchical model that links NPI implementation dates to national case and death counts and supported the results with extensive empirical validation. Closing all educational institutions, limiting gatherings to 10 people or less, and closing face-to-face businesses each reduced transmission considerably. The additional effect of stay-at-home orders was comparatively small.

Prevalence of pretreatment HIV drug resistance in Mwanza, Tanzania.

Background: In a 2008-10 study, we found a pretreatment HIV drug resistance (PDR) prevalence of 18.2% in patients at Bugando Medical Centre (BMC) in Mwanza, Tanzania. Objectives: To determine the prevalence of PDR and transmitted HIV drug resistance (TDR) in patients visiting the BMC from 2013 to 2015. Methods: Adult outpatients were sequentially enrolled into two groups, separated by whether they were initiating ART. Previous exposure to antiretroviral drugs, except for prevention of mother-to-child transmission, was an exclusion criterion. HIV pol sequences were analysed according to WHO guidelines for surveillance of PDR and TDR. Results: Two hundred and thirty-five sequences were analysed (138 ART initiators, 97 non-initiators). The prevalence of PDR was 4.7% (95% CI 2.6%-8.2%) overall, 3.1% (95% CI 1.1%-8.7%) for non-initiators and 5.8% (95% CI 3.0%-11.0%) for ART initiators. PDR to NNRTIs and nucleoside or nucelotide reverse transcriptase inhibitors was found in 3.0% (95% CI 1.5%-6.0%) and 1.7% (95% CI 0.7%-4.3%) of patients, respectively. Resistance to PIs was not observed. The prevalence of TDR was 6.0% (95% CI 3.6%-9.8%). Conclusions: Prevalence of PDR significantly decreased compared with 2008-10 and was below the WHO-defined threshold for triggering a public health response. National and systematic surveillance is needed to inform Tanzania's public health strategy.

Validation of VX2 as a Hepatocellular Carcinoma Model: Comparison of the Molecular Reaction of VX2 and HepG2 Tumor Cells to Sorafenib In Vitro.

As there is currently no superior hepatocellular carcinoma (HCC) model with percutaneous vascular access for transarterial treatments available, the VX2 rabbit model is frequently used for in vivo investigations on liver carcinoma. However, the VX2 cell line was derived from a virus-induced skin papilloma that can form carcinosarcoma in liver of rabbits and the transferability of obtained results to HCC treatment remains open. Here we compared the most frequently investigated human HCC model cell line, HepG2, with VX2 cells in vitro in terms of sensitivity towards the broad specificity kinase inhibitor sorafenib and responsiveness to the addition of platelet-derived growth factor AB (PDGF-AB), vascular endothelial growth factor (VEGF) and hepatic growth factor (HGF), as well as insulin and interleukin-1ß (IL1ß). Phosphorylation of protein kinase B (AKT) the mitogen-activated protein kinases (MAPKs) p38 and p42/44 (extracellular signal-regulated kinase, ERK1/2) and inhibitor of kappa light chain gene enhancer alpha (IĸBα) was determined by western blotting as these events are associated with early signaling cascades. Additionally, the inhibition of phosphorylation under sorafenib treatment was investigated. Sorafenib was equally toxic to both cell lines, but only in HepG2 was activation of caspase 3/7 activity, as a sign of apoptosis, observed. VX2 cells exhibited generally more intense phosphorylation signals in response to the growth factors and also serum. In contrast to VX2, HepG2 cells showed no response to PDGF-AB or VEGF as determined by kinase phosphorylation. In both cell lines, sorafenib inhibited growth factor-induced phosphorylation of ERK and p38-MAPK. AKT phosphorylation was only inhibited in VX2 cells and IĸBα phosphorylation was not influenced by this kinase inhibitor in either cell type. Taken together, the two cellular models for HCC share several features related to sorafenib application, but differed in their responsiveness towards growth factors. Therefore, results obtained with the VX2 model cannot be extended to human HCC without appropriate caution.

Nanoparticles size-dependently initiate self-limiting NETosis-driven inflammation.

The critical size for strong interaction of hydrophobic particles with phospholipid bilayers has been predicted to be 10 nm. Because of the wide spreading of nonpolar nanoparticles (NPs) in the environment, we aimed to reveal the ability of living organisms to entrap NPs via formation of neutrophil extracellular traps (NETs). Upon interaction with various cell types and tissues, 10- to 40-nm-sized NPs induce fast (<20 min) damage of plasma membranes and instability of the lysosomal compartment, leading to the immediate formation of NETs. In contrast, particles sized 100-1,000 nm behaved rather inertly. Resulting NET formation (NETosis) was accompanied by an inflammatory reaction intrinsically endowed with its own resolution, demonstrated in lungs and air pouches of mice. Persistence of small NPs in joints caused unremitting arthritis and bone remodeling. Small NPs coinjected with antigen exerted adjuvant-like activity. This report demonstrates a cellular mechanism that explains how small NPs activate the NETosis pathway and drive their entrapping and resolution of the initial inflammatory response.

New Insights into Neutrophil Extracellular Traps: Mechanisms of Formation and Role in Inflammation.

Recent data suggest that NETosis plays a crucial role in the innate immune response and disturbs the homeostasis of the immune system. NETosis is a form of neutrophil-specific cell death characterized by the release of large web-like structures referred to as neutrophil extracellular traps (NETs). NETs are composed of DNA strands associated with histones and decorated with about 20 different proteins, including neutrophil elastase, myeloperoxidase, cathepsin G, proteinase 3, high mobility group protein B1, and LL37. Reportedly, NETosis can be induced by several microbes, and particulate matter including sterile stimuli, via distinct cellular mechanisms. Meanwhile, suicidal NETosis and vital NETosis are controversial. As we enter the second decade of research on NETosis, we have partly understood NETs as double-edged swords of innate immunity. In this review, we will discuss the mechanisms of NETosis, its antimicrobial action, and role in autoimmune diseases, as well as the relatively new field of NET-associated mitochondrial DNA.

Modified transarterial chemoembolization with locoregional administration of sorafenib for treating hepatocellular carcinoma: feasibility, efficacy, and safety in the VX-2 rabbit liver tumor model.

PURPOSE: We aimed to assess the feasibility, efficacy and safety of a local application of sorafenib within a conventional transarterial chemoembolization in the VX-2 tumor-bearing rabbit model. METHODS: VX-2 tumors were induced in the left liver lobe of 10 New Zealand White rabbits. After two weeks, growth was verified by contrast-enhanced computed tomography (CT). Five rabbits were treated by transarterial chemoembolization using an emulsion of sorafenib and ethiodized oil (referred to as SORATACE; n=5). Rabbits receiving oral sorafenib for two weeks (n=2) and untreated rabbits (n=3) served as controls. After two weeks, contrast-enhanced CT was performed, followed by animal necropsy. RESULTS: The change in tumor diameter between baseline and follow-up was significantly different in the SORATACE group compared with the other groups; tumor shrinkage was observed in the SORATACE group only (P = 0.016). In both control groups, preserved hypervascularity was seen in the follow-up CT in all but one tumor. All tumors in the SORATACE group were devascularized in the follow-up CT. Importantly, substantial parenchymal damage in nontargeted areas of the tumor-bearing liver lobe was seen in rabbits treated with SORATACE. CONCLUSION: SORATACE demonstrated high efficacy in the treatment of experimental VX-2 liver tumors but was also associated with substantial liver parenchymal toxicity.