Genetic and biological characterisation of an avian-like H1N2 swine influenza virus generated by reassortment of circulating avian-like H1N1 and H3N2 subtypes in Denmark

BACKGROUND: The influenza A virus subtypes H1N1, H1N2 and H3N2 are the most prevalent subtypes in swine. In 2003, a reassorted H1N2 swine influenza virus (SIV) subtype appeared and became prevalent in Denmark. In the present study, the reassortant H1N2 subtype was characterised genetically and the infection dynamics compared to an “avian-like” H1N1 virus by an experimental infection study. METHODS: Sequence analyses were performed of the H1N2 virus. Two groups of pigs were inoculated with the reassortant H1N2 virus and an “avian-like” H1N1 virus, respectively, followed by inoculation with the opposite subtype four weeks later. Measurements of HI antibodies and acute phase proteins were performed. Nasal virus excretion and virus load in lungs were determined by real-time RT-PCR. RESULTS: The phylogenetic analysis revealed that the reassorted H1N2 virus contained a European “avian-like” H1-gene and a European “swine-like” N2-gene, thus being genetically distinct from most H1N2 viruses circulating in Europe, but similar to viruses reported in 2009/2010 in Sweden and Italy. Sequence analyses of the internal genes revealed that the reassortment probably arose between circulating Danish “avian-like” H1N1 and H3N2 SIVs. Infected pigs developed cross-reactive antibodies, and increased levels of acute phase proteins after inoculations. Pigs inoculated with H1N2 exhibited nasal virus excretion for seven days, peaking day 1 after inoculation two days earlier than H1N1 infected pigs and at a six times higher level. The difference, however, was not statistically significant. Pigs euthanized on day 4 after inoculation, had a high virus load in all lung lobes. After the second inoculation, the nasal virus excretion was minimal. There were no clinical sign except elevated body temperature under the experimental conditions. CONCLUSIONS: The “avian-like” H1N2 subtype, which has been established in the Danish pig population at least since 2003, is a reassortant between circulating swine “avian-like” H1N1 and H3N2. The Danish H1N2 has an “avian-like” H1 and differs from most other reported H1N2 viruses in Europe and North America/Asia, which have H1-genes of human or “classical-swine” origin, respectively. The variant seems, however, also to be circulating in countries like Sweden and Italy. The infection dynamics of the reassorted “avian-like” H1N2 is similar to the older “avian-like” H1N1 subtype

Explainable Artificial Intelligence and Deep Learning for Analysis and Forecasting of Complex Time Series: Applications to Electricity Prices

A rapid energy transition from fossil fuel based generation to renewable energy sources is vital for the mitigation of climate change but requires complex market structures to manage the coordination of generation and demand. In particular, the German day-ahead market reacts to short-term forecasts one day prior to delivery and is driven by various external drivers. Its understanding and forecasting are essential for the energy transition as it allows renewable energy operators to make profits and promotes key technologies for a stable grid operation, such as battery storage. In this work, we analyze the German day-ahead electricity market using eXplainable Artificial Intelligence (XAI) and forecast electricity prices using deep neural networks. We investigate the application of SHapley Additive exPlanations (SHAP) to study the driving factors of electricity prices. The dataset includes several power system features such as load or renewable forecasts but also fuel prices. Our analysis suggests that load, wind and solar generation are the central external features driving prices, as expected, wherein wind generation affects prices more than solar generation. Simi- larly, fuel prices also highly affect prices in a nontrivial manner. Moreover, large generation ramps are correlated with high prices due to the limited flexibility of nuclear and lignite plants. Based on the results from the XAI method, we establish Long Short-Term Memory (LSTM) networks to forecast electricity prices. We introduce a probabilistic forecast as output, increas- ing the applicability of the model. The LSTM model is able to outperform models from related works and enables additional applications using the predicted standard deviation

The antimicrobial lysine-peptoid hybrid LP5 inhibits DNA replication and induces the SOS response in Staphylococcus aureus

BACKGROUND: The increase in antibiotic resistant bacteria has led to renewed interest in development of alternative antimicrobial compounds such as antimicrobial peptides (AMPs), either naturally-occurring or synthetically-derived. Knowledge of the mode of action (MOA) of synthetic compounds mimicking the function of AMPs is highly valuable both when developing new types of antimicrobials and when predicting resistance development. Despite many functional studies of AMPs, only a few of the synthetic peptides have been studied in detail. RESULTS: We investigated the MOA of the lysine-peptoid hybrid, LP5, which previously has been shown to display antimicrobial activity against Staphylococcus aureus. At concentrations of LP5 above the minimal inhibitory concentration (MIC), the peptoid caused ATP leakage from bacterial cells. However, at concentrations close to the MIC, LP5 inhibited the growth of S. aureus without ATP leakage. Instead, LP5 bound DNA and inhibited macromolecular synthesis. The binding to DNA also led to inhibition of DNA gyrase and topoisomerase IV and caused induction of the SOS response. CONCLUSIONS: Our data demonstrate that LP5 may have a dual mode of action against S. aureus. At MIC concentrations, LP5 binds DNA and inhibits macromolecular synthesis and growth, whereas at concentrations above the MIC, LP5 targets the bacterial membrane leading to disruption of the membrane. These results add new information about the MOA of a new synthetic AMP and aid in the future design of synthetic peptides with increased therapeutic potential