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The erotetic concept involving delusional thinking.
CNS miliary metastasis (MiM) is poorly recognised in breast and other malignancies. Given its rarity, little epidemiologic, radiographic and clinical data are known. Although usually identified on neuroimaging, criteria for radiographic diagnosis do not exist. In this analysis, we establish its presence in breast cancer and identify factors contributing to outcome.

We identified 546 female patients with brain metastasis from breast cancer between 2000 and 2015. Radiographic criteria were established through review of neuroimages by a senior Neuroradiologist, and defined as (1) ≥20 lesions per image on ≥2 non-contiguous MRI images or ≥10 lesions per image on ≥2 non-contiguous CT images, and (2) bilateral lesions located in both the supratentorial and infratentorial compartments.

Twenty-one MiM cases were identified (3.8%). Number and anatomical distribution of metastases best identified MiM, while lesion size did not. Ten patients were diagnosed with MiM as initial CNS metastasis; 11 developed MiM following known CNS metastasis. Breast cancer subtype did not influence MiM development before or after other CNS metastasis.

This is the first study to propose radiographic criteria for MiM diagnosis. Additional analysis is needed to verify data, but our results may enable a standardised approach for future MiM research.
This is the first study to propose radiographic criteria for MiM diagnosis. Additional analysis is needed to verify data, but our results may enable a standardised approach for future MiM research.Although breast cancer brain metastasis is an increasingly common occurrence, relatively little is known about miliary brain metastases, a rare subtype that presents unique diagnostic and management challenges. The present study from Bashour et al. proposes the first objective diagnostic imaging criteria, enabling improved future study.Klebsiella pneumoniae and Escherichia coli are part of the Enterobacteriaceae family, being common sources of community and hospital infections and having high antimicrobial resistance. This resistance profile has become the main problem of public health infections. Determining whether a bacterium has resistance is critical to the correct treatment of the patient. Currently the method for determination of bacterial resistance used in laboratory routine is the antibiogram, whose time to obtain the results can vary from 1 to 3 days. An alternative method to perform this determination faster is excitation-emission matrix (EEM) fluorescence spectroscopy combined with multivariate classification methods. In this paper, Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA) and Support Vector Machines (SVM), coupled with dimensionality reduction and variable selection algorithms Principal Component Analysis (PCA), Genetic Algorithm (GA), and the Successive Projections Algorithm (SPA) were used. The most satisfactory models achieved sensitivity and specificity rates of 100% for all classes, both for E. coli and for K. pneumoniae. This finding demonstrates that the proposed methodology has promising potential in routine analyzes, streamlining the results and increasing the chances of treatment efficiency.We design a framework based on Mask Region-based Convolutional Neural Network to automatically detect and separately extract anatomical components of mosquitoes-thorax, wings, abdomen and legs from images. Our training dataset consisted of 1500 smartphone images of nine mosquito species trapped in Florida. In the proposed technique, the first step is to detect anatomical components within a mosquito image. PRGL493 Then, we localize and classify the extracted anatomical components, while simultaneously adding a branch in the neural network architecture to segment pixels containing only the anatomical components. Evaluation results are favorable. To evaluate generality, we test our architecture trained only with mosquito images on bumblebee images. We again reveal favorable results, particularly in extracting wings. Our techniques in this paper have practical applications in public health, taxonomy and citizen-science efforts.Locally applied vancomycin is increasingly being used in primary hip and knee arthroplasty to reduce the risk of infection. Despite encouraging initial results, considerable debate remains on the basis of the data currently available. In particular, it has been unclear up to now whether local vancomycin is suitable to further reduce the risk of infection even if the rate of infection is already low ( less then  1%). In this monocentric retrospective cohort study, all primary total hip and knee arthroplasties performed between 2013 and 2018 were included. After a change in procedure at the hospital, 1 g vancomycin powder was applied intraarticularly before wound closure. The remaining perioperative procedure was constant over the investigation period. The follow-up was one year. The presence of an infection according to the currently valid MSIS criteria was defined as the endpoint. In patients with TKA two infections (0.3%) were observed under vancomycin prophylaxis in contrast to 44 infections (1.3%) in the control group (p = 0.033). In patients with THA two infections (0.5%) were observed under vancomycin prophylaxis and 48 infections (1.1%) in the control group without local vancomycin but this difference was statistically not significant. No wound complications requiring revision were observed as a result of the vancomycin. On the basis of the results of this study, intraarticular application of vancomycin powder in total hip and knee arthroplasty may be considered. Prospective randomized studies have to confirm this promising results prior a common recommendation.Level of Evidence III Retrospective cohort study.Hydrogen spillover is a well-known phenomenon in heterogeneous catalysis; it involves H2 cleavage on an active metal followed by the migration of dissociated H species over an 'inert' support1-5. Although catalytic hydrogenation using the spilled H species, namely, spillover hydrogenation, has long been proposed, very limited knowledge has been obtained about what kind of support structure is required to achieve spillover hydrogenation1,5. By dispersing Pd atoms onto Cu nanomaterials with different exposed facets, Cu(111) and Cu(100), we demonstrate in this work that while the hydrogen spillover from Pd to Cu is facet independent, the spillover hydrogenation only occurs on Pd1/Cu(100), where the hydrogen atoms spilled from Pd are readily utilized for the semi-hydrogenation of alkynes. This work thus helps to create an effective method for fabricating cost-effective nanocatalysts with an extremely low Pd loading, at the level of 50 ppm, toward the semi-hydrogenation of a broad range of alkynes with extremely high activity and selectivity.
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