Antimicrobial resistance control programmes often aim to "fix" the behaviour of antibiotic users and prescribers. Such behavioural interventions have been widely criticised in social science literature for being inefficient and too narrow in scope. Drawing on these criticisms, this article analyses how political programmes for fixing antibiotic behaviours were adapted into the practices of health-care professionals and patients in Russia. In 2018, we conducted interviews with medical doctors, pharmacists and patients in a Russian city; focusing on their practices around the policy requirement introduced in 2017 which obligated medical prescriptions of antibiotics. We conceptualised the obligatory medical prescription as a political technique which sought to change practices of self-treatment and over-the-counter sales of medications by establishing doctors as an obligatory passage point to access antibiotics. Our analysis shows that the requirement for medical prescriptions does not fulfil the infrastructural gaps that influence antibiotic practices. By navigating the antibiotic prescriptions, doctors, pharmacists and patients informally compensate for the gaps in the existing infrastructure creating informal networks of antibiotic care parallel to the requirement of obligatory prescriptions. Following these informal practices, we could map the inconsistencies in the current policy approaches to tackle AMR as a behavioural rather than infrastructural problem.
  To estimate potential differences in neonatal metabolomic profiles at birth and at the time of newborn screening by delivery mode.
 
  A prospective study at Women's Clinic at Landspitali-The National University Hospital of Iceland. Women having normal vaginal birth or elective caesarean section from November 2013 to April 2014 were offered participation. Blood samples from mothers before birth and umbilical cord at birth were collected and amino acids and acylcarnitines measured by tandem mass spectrometry. Results from the Newborn screening programme in Iceland were collected. Amino acids and acylcarnitines from different samples were compared by delivery mode.
 
  Eighty three normal vaginal births and 32 elective caesarean sections were included. Mean differences at birth were higher for numerous amino acids, and some acylcarnitines in neonates born vaginally compared to elective caesarean section. Maternal blood samples and newborn screening results showed small differences that lost significance after correction for multiple testing. Many amino acids and some acylcarnitines were numerically higher in cord blood compared to maternal.  https://www.selleckchem.com/products/ro-3306.html  Many amino acids and most acylcarnitines were numerically higher in newborn screening results compared to cord blood.
 
  We observed transient yet distinct differences in metabolomic profiles between neonates by delivery mode.
 We observed transient yet distinct differences in metabolomic profiles between neonates by delivery mode.From arid, high desert soil samples collected near Bend, Oregon, 19 unique bacteria were isolated. Each strain was identified by 16S rRNA gene sequencing, and their organic extracts were tested for antibacterial and antiproliferative activities. Noteworthy, six extracts (30 %) exhibited strong inhibition resulting in less than 50 % cell proliferation in more than one cancer cell model, tested at 10 μg/mL. Principal component analysis (PCA) of LC/MS data revealed drastic differences in the metabolic profiles found in the organic extracts of these soil bacteria. In total, fourteen potent antibacterial and/or cytotoxic metabolites were isolated via bioactivity-guided fractionation, including two new natural products a pyrazinone containing tetrapeptide and 7-methoxy-2,3-dimethyl-4H-chromen-4-one, as well as twelve known compounds furanonaphthoquinone I, bafilomycin C1 and D, FD-594, oligomycin A, chloramphenicol, MY12-62A, rac-sclerone, isosclerone, tunicamycin VII, tunicamycin VIII, and (6S,16S)-anthrabenzoxocinone 1.264-C.
  AR-V7-positive metastatic prostate cancer is a lethal phenotype with few treatment options and poor survival.
 
  The two-cohort nonrandomized Phase 2 study of combined immune checkpoint blockade for AR-V7-expressing metastatic castration-resistant prostate cancer (STARVE-PC) evaluated nivolumab (3 mg/kg) plus ipilimumab (1 mg/kg), without (Cohort 1) or with (Cohort 2) the anti-androgen enzalutamide. Co-primary endpoints were safety and prostate-specific antigen (PSA) response rate. Secondary endpoints included time-to-PSA-progression-free survival (PSA-PFS), time-to-clinical/radiographic-PFS, objective response rate (ORR), PFS lasting greater than 24 weeks, and overall survival (OS).
 
  Thirty patients were treated with ipilimumab plus nivolumab (N = 15, Cohort 1, previously reported), or ipilimumab plus nivolumab and enzalutamide (N = 15, Cohort 2) in patients previously progressing on enzalutamide monotherapy. PSA response rate was 2/15 (13%) in cohort 1 and 0/15 in cohort 2, ORR was 2/8 (25%) in Cohort 1 ag IL-17 (HR, 4.53; 95% CI 1.47-13.93) levels. There was a trend towards improved outcomes in men with low sPD-L1 serum levels.
 
  Nivolumab plus ipilimumab demonstrated only modest activity in patients with AR-V7-expressing prostate cancer, and was not sufficient to justify further exploration in unselected patients. Stratification by baseline alkaline phosphatase and cytokines (IL-6, -7, and -17) may be prognostic for outcomes to immunotherapy.
 Nivolumab plus ipilimumab demonstrated only modest activity in patients with AR-V7-expressing prostate cancer, and was not sufficient to justify further exploration in unselected patients. Stratification by baseline alkaline phosphatase and cytokines (IL-6, -7, and -17) may be prognostic for outcomes to immunotherapy.Modeling wildfire activity is crucial for informing science-based risk management and understanding the spatiotemporal dynamics of fire-prone ecosystems worldwide. Models help disentangle the relative influences of different factors, understand wildfire predictability, and provide insights into specific events. Here, we develop Firelihood, a two-component, Bayesian, hierarchically structured, probabilistic model of daily fire activity, which is modeled as the outcome of a marked point process individual fires are the points (occurrence component), and fire sizes are the marks (size component). The space-time Poisson model for occurrence is adjusted to gridded fire counts using the integrated nested Laplace approximation (INLA) combined with the stochastic partial differential equation (SPDE) approach. The size model is based on piecewise-estimated Pareto and generalized Pareto distributions, adjusted with INLA. The Fire Weather Index (FWI) and forest area are the main explanatory variables. Temporal and spatial residuals are included to improve the consistency of the relationship between weather and fire occurrence.