Waterborne Elizabethkingia meningoseptica in adult critical care

Elizabethkingia meningoseptica is an infrequent colonizer of the respiratory tract; its pathogenicity is uncertain. In the context of a 22-month outbreak of E. meningoseptica acquisition affecting 30 patients in a London, UK, critical care unit (3% attack rate) we derived a measure of attributable morbidity and determined whether E. meningoseptica is an emerging nosocomial pathogen. We found monomicrobial E. meningoseptica acquisition (n = 13) to have an attributable morbidity rate of 54% (systemic inflammatory response syndrome >2, rising C-reactive protein, new radiographic changes), suggesting that E. meningoseptica is a pathogen. Epidemiologic and molecular evidence showed acquisition was water-source–associated in critical care but identified numerous other E. meningoseptica strains, indicating more widespread distribution than previously considered. Analysis of changes in gram-negative speciation rates across a wider London hospital network suggests this outbreak, and possibly other recently reported outbreaks, might reflect improved diagnostics and that E. meningoseptica thus is a pseudo-emerging pathogen

Comparative transcriptomics of broad-spectrum and synthetic cannabidiol treated C2C12 skeletal myotubes

Cannabidiol (CBD) is widely used in sports for recovery, pain management, and sleep improvement, yet its effects on muscle are not well understood. This study aimed to determine the transcriptional response of murine skeletal muscle myotubes to broad-spectrum CBD and synthetic CBD (sCBD). Differentiated C2C12 myotubes were treated with 10 μM CBD, sCBD, or vehicle control (DMSO) for 24 h before RNA extraction. Poly-A tail-enriched mRNA libraries were constructed and sequenced using 2 × 50 bp paired-end sequencing. CBD and sCBD treatment induced 4489 and 1979 differentially expressed genes (DEGs; p < 0.001, FDR step-up <0.05), respectively, with common upregulation of 857 genes and common downregulation of 648 genes. Common upregulated DEGs were associated with "response to unfolded protein," "cell redox homeostasis," "endoplasmic reticulum stress," "oxidative stress," and "cellular response to hypoxia." Common downregulated DEGs were linked to "sarcomere organization," "skeletal muscle tissue development," "regulation of muscle contraction," and "muscle contraction." CBD treatment induced unique DEGs compared to sCBD. The data indicate CBD may induce mild cellular stress, activating pathways associated with altered redox balance, unfolded protein response, and endoplasmic reticulum stress. We hypothesize that CBD interacts with muscle and may elicit a "mitohormetic" effect that warrants further investigation

Gait Characterization in Duchenne Muscular Dystrophy (DMD) Using a Single-Sensor Accelerometer: Classical Machine Learning and Deep Learning Approaches

Differences in gait patterns of children with Duchenne muscular dystrophy (DMD) and typically-developing (TD) peers are visible to the eye, but quantifications of those differences outside of the gait laboratory have been elusive. In this work, we measured vertical, mediolateral, and anteroposterior acceleration using a waist-worn iPhone accelerometer during ambulation across a typical range of velocities. Fifteen TD and fifteen DMD children from 3-16 years of age underwent eight walking/running activities, including five 25 meters walk/run speed-calibration tests at a slow walk to running speeds (SC-L1 to SC-L5), a 6-minute walk test (6MWT), a 100 meters fast-walk/jog/run (100MRW), and a free walk (FW). For clinical anchoring purposes, participants completed a Northstar Ambulatory Assessment (NSAA). We extracted temporospatial gait clinical features (CFs) and applied multiple machine learning (ML) approaches to differentiate between DMD and TD children using extracted temporospatial gait CFs and raw data. Extracted temporospatial gait CFs showed reduced step length and a greater mediolateral component of total power (TP) consistent with shorter strides and Trendelenberg-like gait commonly observed in DMD. ML approaches using temporospatial gait CFs and raw data varied in effectiveness at differentiating between DMD and TD controls at different speeds, with an accuracy of up to 100%. We demonstrate that by using ML with accelerometer data from a consumer-grade smartphone, we can capture DMD-associated gait characteristics in toddlers to teens

Characteristics of Patients Who Visit the Emergency Department with Self-Inflicted Injury

During visits to emergency medical facilities, the primary care of and risk identification for individuals who have attempted suicide is considered an important element in suicide prevention. With the ultimate goal of helping to prevent suicide, the aim of the present study was to determine the characteristics of patients with self-inflicted injuries who presented in the emergency department. Patients with self-inflicted injuries who visited 1 of 3 sentinel emergency medical centers from 2007 through 2009 were included in the study. The characteristics, methods, and reasons for suicide attempts were evaluated. Moreover, predictors of severe outcomes were evaluated. A total of 2,996 patients with self-inflicted injuries visited the three centers during a period of 3 yr. The male-to-female suicide ratio was 1:1.38 (P < 0.001). The mean age was 41 yr. Poisoning was the most common method of self-inflicted injury (68.7%) among all age groups. Medication was the primary means of injury in the < 50 age group, and the use of agricultural chemicals was the primary means in the ≥ 50 age group. The reasons for attempting suicide varied among the age groups. The predictors of severe outcome are male gender, older age, and not having consumed alcohol

Cerebrospinal Fluid B Cells Correlate with Early Brain Inflammation in Multiple Sclerosis

Background: There is accumulating evidence from immunological, pathological and therapeutic studies that B cells are key components in the pathophysiology of multiple sclerosis (MS). Methodology/Principal Findings: In this prospective study we have for the first time investigated the differences in the inflammatory response between relapsing and progressive MS by comparing cerebrospinal fluid (CSF) cell profiles from patients at the onset of the disease (clinically isolated syndrome, CIS), relapsing-remitting (RR) and chronic progressive (CP) MS by flow cytometry. As controls we have used patients with other neurological diseases. We have found a statistically significant accumulation of CSF mature B cells (CD19+CD1382) and plasma blasts (CD19+CD138+) in CIS and RRMS. Both B cell populations were, however, not significantly increased in CPMS. Further, this accumulation of B cells correlated with acute brain inflammation measured by magnetic resonance imaging and with inflammatory CSF parameters such as the number of CSF leukocytes, intrathecal immunoglobulin M and G synthesis and intrathecal production of matri

Purification of Nanoparticles by Size and Shape

Producing monodisperse nanoparticles is essential to ensure consistency in biological experiments and to enable a smooth translation into the clinic. Purification of samples into discrete sizes and shapes may not only improve sample quality, but also provide us with the tools to understand which physical properties of nanoparticles are beneficial for a drug delivery vector. In this study, using polymersomes as a model system, we explore four techniques for purifying pre-formed nanoparticles into discrete fractions based on their size, shape or density. We show that these techniques can successfully separate polymersomes into monodisperse fractions

GPS-ARM: Computational Analysis of the APC/C Recognition Motif by Predicting D-Boxes and KEN-Boxes

Anaphase-promoting complex/cyclosome (APC/C), an E3 ubiquitin ligase incorporated with Cdh1 and/or Cdc20 recognizes and interacts with specific substrates, and faithfully orchestrates the proper cell cycle events by targeting proteins for proteasomal degradation. Experimental identification of APC/C substrates is largely dependent on the discovery of APC/C recognition motifs, e.g., the D-box and KEN-box. Although a number of either stringent or loosely defined motifs proposed, these motif patterns are only of limited use due to their insufficient powers of prediction. We report the development of a novel GPS-ARM software package which is useful for the prediction of D-boxes and KEN-boxes in proteins. Using experimentally identified D-boxes and KEN-boxes as the training data sets, a previously developed GPS (Group-based Prediction System) algorithm was adopted. By extensive evaluation and comparison, the GPS-ARM performance was found to be much better than the one using simple motifs. With this powerful tool, we predicted 4,841 potential D-boxes in 3,832 proteins and 1,632 potential KEN-boxes in 1,403 proteins from H. sapiens, while further statistical analysis suggested that both the D-box and KEN-box proteins are involved in a broad spectrum of biological processes beyond the cell cycle. In addition, with the co-localization information, we predicted hundreds of mitosis-specific APC/C substrates with high confidence. As the first computational tool for the prediction of APC/C-mediated degradation, GPS-ARM is a useful tool for information to be used in further experimental investigations. The GPS-ARM is freely accessible for academic researchers at: http://arm.biocuckoo.org

Individualized Cost-Effectiveness Analysis

John Ioannidis and Alan Garber discuss how to use incremental cost-effectiveness ratios (ICER) and related metrics so they can be useful for decision-making at the individual level, whether used by clinicians or individual patients