OBJECTIVE The majority of radiological reports are still written as free text and lack structure. Further evaluation of free-text reports is difficult to achieve without a great deal of manual effort, and is not possible in everyday clinical practice. This study aims to automatically capture clinical information and positive hit rates from narrative radiological reports of suspected urolithiasis using natural language processing (NLP). METHODS Narrative reports of low dose computed tomography (CT) of the retroperitoneum from April 2016 to July 2018 (n = 1714) were analyzed using NLP. These free-text reports were automatically structured based on RadLex concepts. Manual feedback was used to test and train the NLP engine to further enhance the performance. The chi-squared test, phi coefficient, and logistic regression analysis were performed to determine the effect of clinical information on the positive hit rate of urolithiasis. RESULTS Urolithiasis was affirmed in 72 % of the reports; in 38 % at least one stone was described in the kidneys, and in 45 % at least one stone was described in the ureter. Clinical information, such as previous stone history and obstructive uropathy, showed a strong correlation with confirmed urolithiasis (p = 0.001). Previous stone history and the combination of obstructive uropathy and loin pain had the highest association with positive urolithiasis (p less then 0.001). CONCLUSION Applying this NLP approach to already existing free-text reports allows the conversion of such reports into a structured form. This may be valuable for epidemiological studies, to evaluate the appropriateness of CT examinations, or to answer a variety of research questions. BACKGROUND 'Look-alike, sound-alike' (LASA) medicines may be confused by prescribers, pharmacists, nurses and patients, with serious consequences for patient safety. The current research aimed to develop and trial software to proactively identify LASA medicines by computing medicine name similarity scores. METHODS Literature review identified open-source software from the United States Food and Drug Administration for screening of proposed medicine names. We adapted and refined this software to compute similarity scores (0.0000-1.0000) for all possible pairs of medicines registered in Australia. Two-fold exploratory analysis compared RESULTS Screening of the Australian medicines register identified 7,750 medicine pairs with at least moderate (arbitrarily ≥0.6600) name similarity, including many oncology, immunomodulating and neuromuscular-blocking medicines. Computed similarity scores and resulting risk categories demonstrated a modest correlation with the manually-calculated similarity scores (r = 0.324, p less then 0.002, 95 % CI 0.119-0.529). However, agreement between the resulting risk categories was not significant (Cohen's kappa = -0.162, standard error = 0.063). CONCLUSIONS The software (LASA v2) has potential to identify pairs of confusable medicines. It is recommended to supplement incident reports in risk-management programs, and to facilitate pre-screening of medicine names prior to brand/trade name approval and inclusion of medicines in formularies. Crown V. All rights reserved.Staphylococcus aureus is an opportunistic pathogen that normally colonizes the human anterior nares. At the same time, this pathogen is one of the leading causes of life-threatening bloodstream infections, such as sepsis and endocarditis. In this review we will present the current understanding of the pathogenesis of these invasive infections, focusing on the mechanisms of S. aureus clearance from the bloodstream by the immune system, and how this pathogen hijacks the host defense and coagulation systems and further interacts with the blood vessel endothelium. Additionally, we will delve into the regulatory mechanisms S. aureus employs during an invasive infection. These new insights into host-pathogen interactions show promising avenues for the development of novel therapies for treating bloodstream infections. Study of early human embryo development is essential for advancing reproductive and regenerative medicine. Traditional human embryological studies rely on embryonic tissue specimens, which are difficult to acquire due to technical challenges and ethical restrictions. The availability of human stem cells with developmental potentials comparable to pre-implantation and peri-implantation human embryonic and extraembryonic cells, together with properly engineered in vitro culture environments, allow for the first time researchers to generate self-organized multicellular structures in vitro that mimic the structural and molecular features of their in vivo counterparts. The development of these stem cell-based, synthetic human embryo models offers a paradigm-shifting experimental system for quantitative measurements and perturbations of multicellular development, critical for advancing human embryology and reproductive and regenerative medicine without using intact human embryos. Massive use of glyphosate-based herbicides in agricultural activities has led to the appearance of this herbicide in freshwater systems, which represents a potential threat to these systems and their communities. These herbicides can affect autotrophic and heterotrophic picoplankton abundance. However, little is known about glyphosate impact on the whole structure of these assemblages. Herein, we used an 8-day long microcosm approach under indoor controlled conditions to analyze changes in the structure of picoplankton exposed to a single pulse of glyphosate.  https://www.selleckchem.com/products/wnt-c59-c59.html  The analyzed picoplankton correspond to two outdoor ponds with contrasting states "clear" (chlorophyll-a = 3.48 μg L-1± 1.15; nephelometric turbidity, NTU = 1) and "turbid" (chlorophyll-a = 105.96 μg L-1 ± 15.3; NTU = 48). We evaluated herbicide impact on different picoplankton cytometric populations and further explored changes in bacterial dominant operational taxonomic units (OTUs) fingerprinting. We observed that glyphosate induced a drastic decrease in the abundance of phycocyanin-rich picocyanobacteria. Particularly, in the turbid system this effect resulted in an 85 % decrease in the abundance of the whole autotrophic picoplankton. Glyphosate also changed the structure of the heterotrophic fraction by means of changing bacterial dominant OTUs fingerprinting patterns in both systems and by shifting the relative abundances of cytometric groups in the clear scenario. These results demonstrate that upon glyphosate exposure picoplanktonic fractions face not only the already reported changes in abundance, but also alterations in the composition of cytometric groups and of bacterial dominant operational taxonomic units. This research provides suitable and still little explored tools to analyze agrochemical effects on picoplanktonic communities.