Super-spreading Events and Contribution to Transmission of MERS, SARS, and COVID-19

There is no clear definition for the term ‘super-spreader’ or ‘super-spreading event’. The World Health Organization refers to a super-spreader as a patient (or an event) that may transmit infection to a larger number of individuals than is usual by one individual (or event). In the severe acute respiratory syndrome (SARS) situation, a super-spreading event was defined as the transmission of SARS to at ≥8 contacts, and other authors defined this as individuals infecting an unusually large number of secondary cases [ 1 , 2 ]. A super-spreading event could merely be defined as an event in which one patient infects far more people than an average patient does, which is estimated by the basic reproduction number (R0)

Classification enhancement for post-stroke dementia using fuzzy neighborhood preserving analysis with QR-decomposition

The aim of the present study was to discriminate the electroencephalogram (EEG) of 5 patients with vascular dementia (VaD), 15 patients with stroke-related mild cognitive impairment (MCI), and 15 control normal subjects during a working memory (WM) task. We used independent component analysis (ICA) and wavelet transform (WT) as a hybrid preprocessing approach for EEG artifact removal. Three different features were extracted from the cleaned EEG signals: spectral entropy (SpecEn), permutation entropy (PerEn) and Tsallis entropy (TsEn). Two classification schemes were applied - support vector machine (SVM) and k-nearest neighbors (kNN) - with fuzzy neighborhood preserving analysis with QR-decomposition (FNPAQR) as a dimensionality reduction technique. The FNPAQR dimensionality reduction technique increased the SVM classification accuracy from 82.22% to 90.37% and from 82.6% to 86.67% for kNN. These results suggest that FNPAQR consistently improves the discrimination of VaD, MCI patients and control normal subjects and it could be a useful feature selection to help the identification of patients with VaD and MCI

Influence of pH on mechanical relaxations in high solids lm-pectin preparations

The influence of pH on the mechanical relaxation of LM-pectin in the presence of co-solute has been investigated by means of differential scanning calorimetry, ζ-potential measurements and small deformation dynamic oscillation in shear. pH was found to affect the conformational properties of the polyelectrolyte altering its structural behaviour. Cooling scans in the vicinity of the glass transition region revealed a remarkable change in the viscoelastic functions as the polyelectrolyte rearranges from extended (neutral pH) to compact conformations (acidic pH). This conformational rearrangement was experimentally observed to result in early vitrification at neutral pH values where dissociation of galacturonic acid residues takes place. Time-temperature superposition of the mechanical shift factors and theoretical modeling utilizing WLF kinetics confirmed the accelerated kinetics of glass transition in the extended pectin conformation at neutral pH. Determination of the relaxation spectra of the samples using spectral analysis of the master curves revealed that the relaxation of macromolecules occurs within ~0.1 s regardless of the solvent pH

Stroke-related mild cognitive impairment detection during working memory tasks using EEG signal processing

The aim of the present study was to reveal markers from the electroencephalography (EEG) using approximation entropy (ApEn) and permutation entropy (PerEn). EEGs' of 15 stroke-related patients with mild cognitive impairment (MCI) and 15 control healthy subjects during a working memory (WM) task have EEG artifacts were removed using a wavelet (WT) based method. A t-test (p <; 0.05) was used to test the hypothesis that the irregularity (ApEn and PerEn) in MCIs was reduced in comparison with control subjects. ApEn and PerEn showed reduced irregularity in the EEGs of MCI patients. Therefore, ApEn and PerEn could be used as markers associated with MCI detection and identification and the EEG could be a valuable tool for inspecting the background activity in the identification of patients with MCI

EEG markers for early detection and characterization of vascular dementia during working memory tasks

The aim of the this study was to reveal markers using spectral entropy (SpecEn), sample entropy (SampEn) and Hurst Exponent (H) from the electroencephalography (EEG) background activity of 5 vascular dementia (VaD) patients, 15 stroke-related patients with mild cognitive impairment (MCI) and 15 control healthy subjects during a working memory (WM) task. EEG artifacts were removed using independent component analysis technique and wavelet technique. With ANOVA (p < 0.05), SpecEn was used to test the hypothesis of slowing the EEG signal down in both VaD and MCI compared to control subjects, whereas the SampEn and H features were used to test the hypothesis that the irregularity and complexity in both VaD and MCI were reduced in comparison with control subjects. SampEn and H results in reducing the complexity in VaD and MCI patients. Therefore, SampEn could be the EEG marker that associated with VaD detection whereas H could be the marker for stroke-related MCI identification. EEG could be as a valuable marker for inspecting the background activity in the identification of patients with VaD and stroke-related MCI

A Randomized, Double-Blinded, Phase II Trial of Gemcitabine and Nab-Paclitaxel Plus Apatorsen or Placebo in Patients with Metastatic Pancreatic Cancer: The RAINIER Trial.

Lessons learnedThe addition of the heat shock protein 27 (Hsp27)-targeting antisense oligonucleotide, apatorsen, to a standard first-line chemotherapy regimen did not result in improved survival in unselected patients with metastatic pancreatic cancer.Findings from this trial hint at the possible prognostic and predictive value of serum Hsp27 that may warrant further investigation.BackgroundThis randomized, double-blinded, phase II trial evaluated the efficacy of gemcitabine/nab-paclitaxel plus either apatorsen, an antisense oligonucleotide targeting heat shock protein 27 (Hsp27) mRNA, or placebo in patients with metastatic pancreatic cancer.MethodsPatients were randomized 1:1 to Arm A (gemcitabine/nab-paclitaxel plus apatorsen) or Arm B (gemcitabine/nab-paclitaxel plus placebo). Treatment was administered in 28-day cycles, with restaging every 2 cycles, until progression or intolerable toxicity. Serum Hsp27 levels were analyzed at baseline and on treatment. The primary endpoint was overall survival (OS).ResultsOne hundred thirty-two patients were enrolled, 66 per arm. Cytopenias and fatigue were the most frequent grade 3/4 treatment-related adverse events for both arms. Median progression-free survival (PFS) and OS were 2.7 and 5.3 months, respectively, for arm A, and 3.8 and 6.9 months, respectively, for arm B. Objective response rate was 18% for both arms. Patients with high serum level of Hsp27 represented a poor-prognosis subgroup who may have derived modest benefit from addition of apatorsen.ConclusionAddition of apatorsen to chemotherapy does not improve outcomes in unselected patients with metastatic pancreatic cancer in the first-line setting, although a trend toward prolonged PFS and OS in patients with high baseline serum Hsp27 suggests this therapy may warrant further evaluation in this subgroup

T helper cell subsets specific for pseudomonas aeruginosa in healthy individuals and patients with cystic fibrosis

Background: We set out to determine the magnitude of antigen-specific memory T helper cell responses to Pseudomonas aeruginosa in healthy humans and patients with cystic fibrosis. Methods: Peripheral blood human memory CD4+ T cells were co-cultured with dendritic cells that had been infected with different strains of Pseudomonas aeruginosa. The T helper response was determined by measuring proliferation, immunoassay of cytokine output, and immunostaining of intracellular cytokines. Results: Healthy individuals and patients with cystic fibrosis had robust antigen-specific memory CD4+ T cell responses to Pseudomonas aeruginosa that not only contained a Th1 and Th17 component but also Th22 cells. In contrast to previous descriptions of human Th22 cells, these Pseudomonal-specific Th22 cells lacked the skin homing markers CCR4 or CCR10, although were CCR6+. Healthy individuals and patients with cystic fibrosis had similar levels of Th22 cells, but the patient group had significantly fewer Th17 cells in peripheral blood. Conclusions: Th22 cells specific to Pseudomonas aeruginosa are induced in both healthy individuals and patients with cystic fibrosis. Along with Th17 cells, they may play an important role in the pulmonary response to this microbe in patients with cystic fibrosis and other conditions

Image informatics strategies for deciphering neuronal network connectivity

Brain function relies on an intricate network of highly dynamic neuronal connections that rewires dramatically under the impulse of various external cues and pathological conditions. Among the neuronal structures that show morphologi- cal plasticity are neurites, synapses, dendritic spines and even nuclei. This structural remodelling is directly connected with functional changes such as intercellular com- munication and the associated calcium-bursting behaviour. In vitro cultured neu- ronal networks are valuable models for studying these morpho-functional changes. Owing to the automation and standardisation of both image acquisition and image analysis, it has become possible to extract statistically relevant readout from such networks. Here, we focus on the current state-of-the-art in image informatics that enables quantitative microscopic interrogation of neuronal networks. We describe the major correlates of neuronal connectivity and present workflows for analysing them. Finally, we provide an outlook on the challenges that remain to be addressed, and discuss how imaging algorithms can be extended beyond in vitro imaging studies

Local variation of hashtag spike trains and popularity in Twitter

We draw a parallel between hashtag time series and neuron spike trains. In each case, the process presents complex dynamic patterns including temporal correlations, burstiness, and all other types of nonstationarity. We propose the adoption of the so-called local variation in order to uncover salient dynamics, while properly detrending for the time-dependent features of a signal. The methodology is tested on both real and randomized hashtag spike trains, and identifies that popular hashtags present regular and so less bursty behavior, suggesting its potential use for predicting online popularity in social media.Comment: 7 pages, 7 figure