Little difference between minimum inhibitory concentrations of Mycobacterium tuberculosis wild-type organisms determined with BACTEC MGIT 960 and Middlebrook 7H10

AbstractThe MIC wild-type (WT) distribution for Mycobacterium tuberculosis in BACTEC 960 MGIT is not defined, which may result in poor reproducibility for drug susceptibility testing (DST), as several DST methods with different breakpoints are in use. In a comparison between MGIT and Middlebrook 7H10 medium of seven first- and second-line drugs, including 133 MIC determinations of 15 WT isolates, we found an agreement of 91.7% within ± one MIC dilution step. The results confirm the agreement in MIC testing between 7H10 and MGIT and indicate that breakpoints could be harmonized in order to avoid misclassification

Biofidelic image registration for head and neck region utilizing an in-silico articulated skeleton as a transformation model

Objective. We propose an integration scheme for a biomechanical motion model into a deformable image registration. We demonstrate its accuracy and reproducibility for adaptive radiation therapy in the head and neck region. Approach. The novel registration scheme for the bony structures in the head and neck regions is based on a previously developed articulated kinematic skeleton model. The realized iterative single-bone optimization process directly triggers posture changes of the articulated skeleton, exchanging the transformation model within the deformable image registration process. Accuracy in terms of target registration errors in the bones is evaluated for 18 vector fields of three patients between each planning CT and six fraction CT scans distributed along the treatment course. Main results. The median of target registration error distribution of the landmark pairs is 1.4 ± 0.3 mm. This is sufficient accuracy for adaptive radiation therapy. The registration performs equally well for all three patients and no degradation of the registration accuracy can be observed throughout the treatment. Significance. Deformable image registration, despite its known residual uncertainties, is until now the tool of choice towards online re-planning automation. By introducing a biofidelic motion model into the optimization, we provide a viable way towards an in-build quality assurance

Carbapenem-non-susceptible Enterobacteriaceae in Europe : conclusions from a meeting of national experts

The emergence and global spread of carbapenemase-producing Enterobacteriaceae is of great concern to health services worldwide. These bacteria are often resistant to all beta-lactam antibiotics and frequently co-resistant to most other antibiotics, leaving very few treatment options. The epidemiology is compounded by the diversity of carbapenem-hydrolysing enzymes and the ability of their genes to spread between different bacterial species. Difficulties are also encountered by laboratories when trying to detect carbapenemase production during routine diagnostic procedures due to an often heterogeneous expression of resistance. Some of the resistance genes are associated with successful clonal lineages which have a selective advantage in those hospitals where antimicrobial use is high and opportunities for transmission exist; others are more often associated with transmissible plasmids. A genetically distinct strain of Klebsiella pneumoniae sequence type (ST) 258 harbouring the K. Pneumoniae carbapenemases (KPC) has been causing epidemics of national and international proportions. It follows the pathways of patient referrals, causing hospital outbreaks along the way. Simultaneously, diverse strains harbouring New Delhi metallo-beta-lactamase (NDM-1) are repeatedly being imported into Europe, commonly via patients with prior medical exposure in the Indian subcontinent. Since the nature and scale of carbapenem-non-susceptible Entrobacteriaceae as a threat to hospital patients in Europe remains unclear, a consultation of experts from 31 countries set out to identify the gaps in diagnostic and response capacity, to index the magnitude of carbapenem-non-susceptibility across Europe using a novel five-level staging system, and to provide elements of a strategy to combat this public health issue in a concerted manner.peer-reviewe

Polymorphisms in genes involved in estrogen and progesterone metabolism and mammographic density changes in women randomized to postmenopausal hormone therapy: results from a pilot study

INTRODUCTION: Mammographic density is a strong independent risk factor for breast cancer, and can be modified by hormonal exposures. Identifying genetic variants that determine increases in mammographic density in hormone users may be important in understanding hormonal carcinogenesis of the breast. METHODS: We obtained mammograms and DNA from 232 postmenopausal women aged 45 to 75 years who had participated in one of two randomized, double-blind clinical trials with estrogen therapy (104 women, taking 1 mg/day of micronized 17β-estradiol, E2), combined estrogen and progestin therapy (34 women, taking 17β-estradiol and 5 mg/day of medroxyprogesterone acetate for 12 days/month) or matching placebos (94 women). Mammographic percentage density (MPD) was measured on baseline and 12-month mammograms with a validated computer-assisted method. We evaluated polymorphisms in genes involved in estrogen metabolism (catechol-O-methyltransferase (COMT (Val158Met)), cytochrome P450 1B1 (CYP1B1 (Val432Leu)), UDP-glucuronosyltransferase 1A1 (UGT1A1 (<7/≥ 7 TA repeats))) and progesterone metabolism (aldo-keto reductase 1C4 (AKR1C4 (Leu311Val))) with changes in MPD. RESULTS: The adjusted mean change in MPD was +4.6% in the estrogen therapy arm and +7.2% in the combined estrogen and progestin therapy arm, compared with +0.02% in the placebo arm (P = 0.0001). None of the genetic variants predicted mammographic density changes in women using estrogen therapy. Both the AKR1C4 and the CYP1B1 polymorphisms predicted mammographic density change in the combined estrogen and progestin therapy group (P < 0.05). In particular, the eight women carrying one or two low-activity AKR1C4 Val alleles showed a significantly greater increase in MPD (16.7% and 29.3%) than women homozygous for the Leu allele (4.0%). CONCLUSION: Although based on small numbers, these findings suggest that the magnitude of the increase in mammographic density in women using combined estrogen and progestin therapy may be greater in those with genetically determined lower activity of enzymes that metabolize estrogen and progesterone

The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism

© 2020, University of Surrey. All rights reserved. The Overview, Design concepts and Details (ODD) protocol for describing Individual-and Agent-Based Models (ABMs) is now widely accepted and used to document such models in journal articles. As a standardized document for providing a consistent, logical and readable account of the structure and dynamics of ABMs, some research groups also find it useful as a workflow for model design. Even so, there are still limitations to ODD that obstruct its more widespread adoption. Such limitations are discussed and addressed in this paper: the limited availability of guidance on how to use ODD; the length of ODD documents; limitations of ODD for highly complex models; lack of sufficient details of many ODDs to enable reimplementation without access to the model code; and the lack of provision for sections in the document structure covering model design ratio-nale, the model’s underlying narrative, and the means by which the model’s fitness for purpose is evaluated. We document the steps we have taken to provide better guidance on: structuring complex ODDs and an ODD summary for inclusion in a journal article (with full details in supplementary material; Table 1); using ODD to point readers to relevant sections of the model code; update the document structure to include sections on model rationale and evaluation. We also further advocate the need for standard descriptions of simulation experiments and argue that ODD can in principle be used for any type of simulation model. Thereby ODD would provide a lingua franca for simulation modelling

EUCAST expert rules in antimicrobial susceptibility testing

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