Ultra-Fast and Optimized Method for the Preparation of Rodent Testicular Cells for Flow Cytometric Analysis

Homogeneity of cell populations is a prerequisite for the analysis of biochemical and molecular events during male gamete differentiation. Given the complex organization of the mammalian testicular tissue, various methods have been used to obtain enriched or purified cell populations, including flow cell sorting. Current protocols are usually time-consuming and may imply loss of short-lived RNAs, which is undesirable for expression profiling. We describe an optimized method to speed up the preparation of suitable testicular cell suspensions for cytometric analysis of different spermatogenic stages from rodents. The procedure takes only 15 min including testis dissection, tissue cutting, and processing through the Medimachine System (Becton Dickinson). This method could be a substitute for the more tedious and time-consuming cell preparation techniques currently in use

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Predicting Bipolar Disorder Risk Factors in Distressed Young Adults From Patterns of Brain Activation to Reward: A Machine Learning Approach

BACKGROUND: The aim of this study was to apply multivariate pattern recognition to predict the severity of behavioral traits and symptoms associated with risk for bipolar spectrum disorder from patterns of whole-brain activation during reward expectancy to facilitate the identification of individual-level neural biomarkers of bipolar disorder risk. METHODS: We acquired functional neuroimaging data from two independent samples of transdiagnostically recruited adults (18-25 years of age; n = 56, mean age 21.9 ± 2.2 years, 42 women; n = 36, mean age 21.2 ± 2.2 years, 24 women) during reward expectancy task performance. Pattern recognition model performance in each sample was measured using correlation and mean squared error between actual and whole-brain activation-predicted scores on behavioral traits and symptoms. RESULTS: In the first sample, the model significantly predicted severity of a specific hypo/mania-related symptom, heightened energy, measured by the energy manic subdomain of the Mood Spectrum Structured Interviews (r = .42, p = .001; mean squared error = 9.93, p = .001). The region with the highest contribution to the model was the left ventrolateral prefrontal cortex. Results were confirmed in the second sample (r = .33, p = .01; mean squared error = 8.61, p = .01), in which the severity of this symptom was predicted using a bilateral ventrolateral prefrontal cortical mask (r = .33, p = .009, mean squared error = 9.37, p = .04). CONCLUSIONS: The severity of a specific hypo/mania-related symptom was predicted from patterns of whole-brain activation in two independent samples. Given that emerging manic symptoms predispose to bipolar disorders, these findings could provide neural biomarkers to aid early identification of individual-level bipolar disorder risk in young adults

Gastrointestinal function in intensive care patients: terminology, definitions and management. Recommendations of the ESICM Working Group on Abdominal Problems

Acute gastrointestinal (GI) dysfunction and failure have been increasingly recognized in critically ill patients. The variety of definitions proposed in the past has led to confusion and difficulty in comparing one study to another. An international working group convened to standardize the definitions for acute GI failure and GI symptoms and to review the therapeutic options

Mathematical Model of Plasmid-Mediated Resistance to Ceftiofur in Commensal Enteric Escherichia coli of Cattle

Antimicrobial use in food animals may contribute to antimicrobial resistance in bacteria of animals and humans. Commensal bacteria of animal intestine may serve as a reservoir of resistance-genes. To understand the dynamics of plasmid-mediated resistance to cephalosporin ceftiofur in enteric commensals of cattle, we developed a deterministic mathematical model of the dynamics of ceftiofur-sensitive and resistant commensal enteric Escherichia coli (E. coli) in the absence of and during parenteral therapy with ceftiofur. The most common treatment scenarios including those using a sustained-release drug formulation were simulated; the model outputs were in agreement with the available experimental data. The model indicated that a low but stable fraction of resistant enteric E. coli could persist in the absence of immediate ceftiofur pressure, being sustained by horizontal and vertical transfers of plasmids carrying resistance-genes, and ingestion of resistant E. coli. During parenteral therapy with ceftiofur, resistant enteric E. coli expanded in absolute number and relative frequency. This expansion was most influenced by parameters of antimicrobial action of ceftiofur against E. coli. After treatment (>5 weeks from start of therapy) the fraction of ceftiofur-resistant cells among enteric E. coli, similar to that in the absence of treatment, was most influenced by the parameters of ecology of enteric E. coli, such as the frequency of transfer of plasmids carrying resistance-genes, the rate of replacement of enteric E. coli by ingested E. coli, and the frequency of ceftiofur resistance in the latter

Accounting for dynamic fluctuations across time when examining fMRI test-retest reliability: Analysis of a reward paradigm in the EMBARC study

Longitudinal investigation of the neural correlates of reward processing in depression may represent an important step in defining effective biomarkers for antidepressant treatment outcome prediction, but the reliability of reward-related activation is not well understood. Thirty-seven healthy control participants were scanned using fMRI while performing a reward-related guessing task on two occasions, approximately one week apart. Two main contrasts were examined: right ventral striatum (VS) activation fMRI BOLD signal related to signed prediction errors (PE) and reward expectancy (RE). We also examined bilateral visual cortex activation coupled to outcome anticipation. Significant VS PE-related activity was observed at the first testing session, but at the second testing session, VS PE-related activation was significantly reduced. Conversely, significant VS RE-related activity was observed at time 2 but not time 1. Increases in VS RE-related activity from time 1 to time 2 were significantly associated with decreases in VS PE-related activity from time 1 to time 2 across participants. Intraclass correlations (ICCs) in VS were very low. By contrast, visual cortex activation had much larger ICCs, particularly in individuals with high quality data. Dynamic changes in brain activation are widely predicted, and failure to account for these changes could lead to inaccurate evaluations of the reliability of functional MRI signals. Conventional measures of reliability cannot distinguish between changes specified by algorithmic models of neural function and noisy signal. Here, we provide evidence for the former possibility: reward-related VS activations follow the pattern predicted by temporal difference models of reward learning but have low ICCs

Discovering Cooperative Relationships of Chromatin Modifications in Human T Cells Based on a Proposed Closeness Measure

BACKGROUND: Eukaryotic transcription is accompanied by combinatorial chromatin modifications that serve as functional epigenetic markers. Composition of chromatin modifications specifies histone codes that regulate the associated gene. Discovering novel chromatin regulatory relationships are of general interest. METHODOLOGY/PRINCIPAL FINDINGS: Based on the premise that the interaction of chromatin modifications is hypothesized to influence CpG methylation, we present a closeness measure to characterize the regulatory interactions of epigenomic features. The closeness measure is applied to genome-wide CpG methylation and histone modification datasets in human CD4+T cells to select a subset of potential features. To uncover epigenomic and genomic patterns, CpG loci are clustered into nine modules associated with distinct chromatin and genomic signatures based on terms of biological function. We then performed Bayesian network inference to uncover inherent regulatory relationships from the feature selected closeness measure profile and all nine module-specific profiles respectively. The global and module-specific network exhibits topological proximity and modularity. We found that the regulatory patterns of chromatin modifications differ significantly across modules and that distinct patterns are related to specific transcriptional levels and biological function. DNA methylation and genomic features are found to have little regulatory function. The regulatory relationships were partly validated by literature reviews. We also used partial correlation analysis in other cells to verify novel regulatory relationships. CONCLUSIONS/SIGNIFICANCE: The interactions among chromatin modifications and genomic elements characterized by a closeness measure help elucidate cooperative patterns of chromatin modification in transcriptional regulation and help decipher complex histone codes

An Aggregate MapReduce Data Block Placement Strategy for Wireless IoT Edge Nodes in Smart Grid

Big data analytics has simplified processing complexity of large dataset in a distributed environment. Many state-of-the-art platforms i.e. smart grid has adopted the processing structure of big data and manages a large volume of data through MapReduce paradigm at distribution ends. Thus, whenever a wireless IoT edge node bundles a sensor dataset into storage media, MapReduce agent performs analytics and generates output into the grid repository. This practice has efficiently reduced the consumption of resources in such a giant network and strengthens other components of the smart grid to perform data analytics through aggregate programming. However, it consumes an operational latency of accessing large dataset from a central repository. As we know that, smart grid processes I/O operations of multi-homing networks, therefore, it accesses large datasets for processing MapReduce jobs at wireless IoT edge nodes. As a result, aggregate MapReduce at wireless IoT edge node produces a network congestion and operational latency problem. To overcome this issue, we propose Wireless IoT Edge-enabled Block Replica Strategy (WIEBRS), that stores in-place, partition-based and multi-homing block replica to respective edge nodes. This reduces the delay latency of accessing datasets for aggregate MapReduce and increases the performance of the job in the smart grid. The simulation results show that WIEBRS effective decreases operational latency with an increment of aggregate MapReduce job performance in the smart grid