Clindamycin adjunctive therapy for severe Staphylococcus aureus treatment evaluation (CASSETTE)—an open-labelled pilot randomized controlled trial

Background Combination antibiotic therapy with an antitoxin agent, such as clindamycin, is included in some guidelines for severe, toxin-mediated Staphylococcus aureus infections. The evidence to support this practice is currently limited to in vitro, animal and observational human case-series data, with no previous randomized controlled trials (RCTs). Objectives This pilot RCT aimed to determine the feasibility of conducting a clinical trial to examine if adjunctive clindamycin with standard therapy has greater efficacy than standard therapy alone for S. aureus infections. Methods We performed an investigator-initiated, open-label, multicentre, pilot RCT (ACTRN12617001416381p) in adults and children with severe S. aureus infections, randomized to standard antibiotic therapy with or without clindamycin for 7 days. Results Over 28 months, across nine sites, 127 individuals were screened and 34 randomized, including 11 children (32%). The primary outcome—number of days alive and free of systemic inflammatory response syndrome ≤14 days—was similar between groups: clindamycin (3 days [IQR 1–6]) versus standard therapy (4 days [IQR 0–8]). The 90 day mortality was 0% (0/17) in the clindamycin group versus 24% (4/17) in the standard therapy group. Secondary outcomes—microbiological relapse, treatment failure or diarrhoea—were similar between groups. Conclusions As the first clinical trial assessing adjunctive clindamycin for S. aureus infections, this study indicates feasibility and that adults and children can be incorporated into one trial using harmonized endpoints, and there were no safety concerns. The CASSETTE trial will inform the definitive S. aureus Network Adaptive Platform (SNAP) trial, which includes an adjunctive clindamycin domain and participants with non-severe disease

Robust and prototypical immune responses toward COVID-19 vaccine in First Nations peoples are impacted by comorbidities

High-risk groups, including Indigenous people, are at risk of severe COVID-19. Here we found that Australian First Nations peoples elicit effective immune responses to COVID-19 BNT162b2 vaccination, including neutralizing antibodies, receptor-binding domain (RBD) antibodies, SARS-CoV-2 spike-specific B cells, and CD4+ and CD8+ T cells. In First Nations participants, RBD IgG antibody titers were correlated with body mass index and negatively correlated with age. Reduced RBD antibodies, spike-specific B cells and follicular helper T cells were found in vaccinated participants with chronic conditions (diabetes, renal disease) and were strongly associated with altered glycosylation of IgG and increased interleukin-18 levels in the plasma. These immune perturbations were also found in non-Indigenous people with comorbidities, indicating that they were related to comorbidities rather than ethnicity. However, our study is of a great importance to First Nations peoples who have disproportionate rates of chronic comorbidities and provides evidence of robust immune responses after COVID-19 vaccination in Indigenous people

Risk prediction system for dengue transmission based on high resolution weather data

BACKGROUND: Dengue is the fastest spreading vector-borne viral disease, resulting in an estimated 390 million infections annually. Precise prediction of many attributes related to dengue is still a challenge due to the complex dynamics of the disease. Important attributes to predict include: the risk of and risk factors for an infection; infection severity; and the timing and magnitude of outbreaks. In this work, we build a model for predicting the risk of dengue transmission using high-resolution weather data. The level of dengue transmission risk depends on the vector density, hence we predict risk via vector prediction. METHODS AND FINDINGS: We make use of surveillance data on Aedes aegypti larvae collected by the Taiwan Centers for Disease Control as part of the national routine entomological surveillance of dengue, and weather data simulated using the IBM's Containerized Forecasting Workflow, a high spatial- and temporal-resolution forecasting system. We propose a two stage risk prediction system for assessing dengue transmission via Aedes aegypti mosquitoes. In stage one, we perform a logistic regression to determine whether larvae are present or absent at the locations of interest using weather attributes as the explanatory variables. The results are then aggregated to an administrative division, with presence in the division determined by a threshold percentage of larvae positive locations resulting from a bootstrap approach. In stage two, larvae counts are estimated for the predicted larvae positive divisions from stage one, using a zero-inflated negative binomial model. This model identifies the larvae positive locations with 71% accuracy and predicts the larvae numbers producing a coverage probability of 98% over 95% nominal prediction intervals. This two-stage model improves the overall accuracy of identifying larvae positive locations by 29%, and the mean squared error of predicted larvae numbers by 9.6%, against a single-stage approach which uses a zero-inflated binomial regression approach. CONCLUSIONS: We demonstrate a risk prediction system using high resolution weather data can provide valuable insight to the distribution of risk over a geographical region. The work also shows that a two-stage approach is beneficial in predicting risk in non-homogeneous regions, where the risk is localised

Reinforcement Learning Agents Playing Ticket to Ride-A Complex Imperfect Information Board Game With Delayed Rewards

Board games are extensively studied in the AI community because of their ability to reflect/represent real-world problems with a high-level of abstraction, and their irreplaceable role as testbeds of state-of-the-art AI algorithms. Modern board games are commonly featured with partially observable state spaces and imperfect information. Despite some recent successes in AI tackling perfect information board games like chess and Go, most imperfect information games are still challenging and have yet to be solved. This paper empirically explores the capabilities of a state-of-the-art Reinforcement Learning (RL) algorithm - Proximal Policy Optimization (PPO) in playing Ticket to Ride, a popular board game with features of imperfect information, large state-action space, and delayed rewards. This paper explores the feasibility of the proposed generalizable modelling and training schemes using a general-purpose RL algorithm with no domain knowledge-based heuristics beyond game rules, game states and scores to tackle this complex imperfect information game. The performance of the proposed methodology is demonstrated in a scaled-down version of Ticket to Ride with a range of RL agents obtained with different training schemes. All RL agents achieve clear advantages over a set of well-designed heuristic agents. The agent constructed through a self-play training scheme outperforms the other RL agents in a Round Robin tournament. The high performance and versality of this self-play agent provide a solid demonstration of the capabilities of this framework

Handlungsempfehlungen zur Umsetzung des UN ECE-Uebereinkommens ueber die Umweltvertraeglichkeitspruefung im grenzueberschreitenden Rahmen (Beispiel deutsch-tschechischer Grenzraum) Entwurf fuer ein Informationshandbuch mit Angaben zu Rechtlichen Grundlagen, Verwaltungsaufbau und Zustaendigkeiten, Schutzguetern, Erfahrungen, Adressen. Endbericht T. 1: Informationshandbuch

Also published in Czech, report no. UBA-FB--000129/czAvailable from TIB Hannover: RN 8908(2000,129) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Umwelt, Naturschutz und Reaktorsicherheit, Bonn (Germany)DEGerman

The Darwin Prospective Melioidosis Study: a 30-year prospective, observational investigation

Background The global distribution of melioidosis is under considerable scrutiny, with both unmasking of endemic disease in African and Pacific nations and evidence of more recent dispersal in the Americas. Because of the high incidence of disease in tropical northern Australia, The Darwin Prospective Melioidosis Study commenced in October, 1989. We present epidemiology, clinical features, outcomes, and bacterial genomics from this 30-year study, highlighting changes in the past decade. Methods The present study was a prospective analysis of epidemiological, clinical, and laboratory data for all culture-confirmed melioidosis cases from the tropical Northern Territory of Australia from Oct 1, 1989, until Sept 30, 2019. Cases were identified on the basis of culture-confirmed melioidosis, a laboratory-notifiable disease in the Northern Territory of Australia. Patients who were culture-positive were included in the study. Multivariable analysis determined predictors of clinical presentations and outcome. Incidence, survival, and cluster analyses were facilitated by population and rainfall data and genotyping of Burkholderia pseudomallei, including multilocus sequence typing and whole-genome sequencing. Findings There were 1148 individuals with culture-confirmed melioidosis, of whom 133 (12%) died. Median age was 50 years (IQR 38–60), 48 (4%) study participants were children younger than 15 years of age, 721 (63%) were male individuals, and 600 (52%) Indigenous Australians. All but 186 (16%) had clinical risk factors, 513 (45%) had diabetes, and 455 (40%) hazardous alcohol use. Only three (2%) of 133 fatalities had no identified risk. Pneumonia was the most common presentation occurring in 595 (52%) patients. Bacteraemia occurred in 633 (56%) of 1135 patients, septic shock in 240 (21%) patients, and 180 (16%) patients required mechanical ventilation. Cases correlated with rainfall, with 80% of infections occurring during the wet season (November to April). Median annual incidence was 20·5 cases per 100 000 people; the highest annual incidence in Indigenous Australians was 103·6 per 100 000 in 2011–12. Over the 30 years, annual incidences increased, as did the proportion of patients with diabetes, although mortality decreased to 17 (6%) of 278 patients over the past 5 years. Genotyping of B pseudomallei confirmed case clusters linked to environmental sources and defined evolving and new sequence types. Interpretation Melioidosis is an opportunistic infection with a diverse spectrum of clinical presentations and severity. With early diagnosis, specific antimicrobial therapy, and state-of-the-art intensive care, mortality can be reduced to less than 10%. However, mortality remains much higher in the many endemic regions where health resources remain scarce. Genotyping of B pseudomallei informs evolving local and global epidemiology. Funding The Australian National Health and Medical Research Council

Handlungsempfehlungen zur Umsetzung des UN ECE-Uebereinkommens ueber die Umweltvertraeglichkeitspruefung im grenzueberschreitenden Rahmen (Beispiel deutsch-tschechischer Grenzraum). T. 1: Informationshandbuch

Also published as UBA-Texte 55/00 in Czech: Doporuceny postup pri transpozici umluvy UN ECE o posuzovani vlivu na zivotni prostredi (EIA) v preshranicnim kontextuAvailable from TIB Hannover: RN 8422(2000,54): RN 8422(2000,55) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Umwelt, Naturschutz und Reaktorsicherheit, Bonn (Germany)DEGerman

Bodenbelastungen in Verdichtungsgebieten am Beispiel Berlin (West) und Grossraum Hannover Endbericht

TIB Hannover: FR 4244+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman