Slower alpha rhythm associates with poorer seizure control in epilepsy.

OBJECTIVE: Slowing and frontal spread of the alpha rhythm have been reported in multiple epilepsy syndromes. We investigated whether these phenomena are associated with seizure control. METHODS: We prospectively acquired resting-state electroencephalogram (EEG) in 63 patients with focal and idiopathic generalized epilepsy (FE and IGE) and 39 age- and gender-matched healthy subjects (HS). Patients were divided into good and poor (≥4 seizures/12 months) seizure control groups based on self-reports and clinical records. We computed spectral power from 20-sec EEG segments during eyes-closed wakefulness, free of interictal abnormalities, and quantified power in high- and low-alpha bands. Analysis of covariance and post hoc t-tests were used to assess group differences in alpha-power shift across all EEG channels. Permutation-based statistics were used to assess the topography of this shift across the whole scalp. RESULTS: Compared to HS, patients showed a statistically significant shift of spectral power from high- to low-alpha frequencies (effect size g = 0.78 [95% confidence interval 0.43, 1.20]). This alpha-power shift was driven by patients with poor seizure control in both FE and IGE (g = 1.14, [0.65, 1.74]), and occurred over midline frontal and bilateral occipital regions. IGE exhibited less alpha power shift compared to FE over bilateral frontal regions (g = -1.16 [-0.68, -1.74]). There was no interaction between syndrome and seizure control. Effects were independent of antiepileptic drug load, time of day, or subgroup definitions. INTERPRETATION: Alpha slowing and anteriorization are a robust finding in patients with epilepsy and might represent a generic indicator of seizure liability

Defining hypoxaemia from pulse oximeter measurements of oxygen saturation in well children at low altitude in Bangladesh: an observational study

BACKGROUND: WHO defines hypoxaemia, a low peripheral arterial oxyhaemoglobin saturation (SpO2), as <90%. Although hypoxaemia is an important risk factor for mortality of children with respiratory infections, the optimal SpO2 threshold for defining hypoxaemia is uncertain in low-income and middle-income countries (LMICs). We derived a SpO2 threshold for hypoxaemia from well children in Bangladesh residing at low altitude. METHODS: We prospectively enrolled well, children aged 3-35 months participating in a pneumococcal vaccine evaluation in Sylhet district, Bangladesh between June and August 2017. Trained health workers conducting community surveillance measured the SpO2 of children using a Masimo Rad-5 pulse oximeter with a wrap sensor. We used standard summary statistics to evaluate the SpO2 distribution, including whether the distribution differed by age or sex. We considered the 2.5th, 5th and 10th percentiles of SpO2 as possible lower thresholds for hypoxaemia. RESULTS: Our primary analytical sample included 1470 children (mean age 18.6±9.5 months). Median SpO2 was 98% (IQR 96%-99%), and the 2.5th, 5th and 10th percentile SpO2 was 91%, 92% and 94%. No child had a SpO2 <90%. Children 3-11 months had a lower median SpO2 (97%) than 12-23 months (98%) and 24-35 months (98%) (p=0.039). The SpO2 distribution did not differ by sex (p=0.959). CONCLUSION: A SpO2 threshold for hypoxaemia derived from the 2.5th, 5th or 10th percentile of well children is higher than <90%. If a higher threshold than <90% is adopted into LMIC care algorithms then decision-making using SpO2 must also consider the child's clinical status to minimise misclassification of well children as hypoxaemic. Younger children in lower altitude LMICs may require a different threshold for hypoxaemia than older children. Evaluating the mortality risk of sick children using higher SpO2 thresholds for hypoxaemia is a key next step

Bovine Herpesvirus Type 1 (BHV-1) UL49.5 Luminal Domain Residues 30 to 32 Are Critical for MHC-I Down-Regulation in Virus-Infected Cells

Bovine herpesvirus type 1 (BHV-1) UL49.5 inhibits transporter associated with antigen processing (TAP) and down-regulates cell-surface expression of major histocompatibility complex (MHC) class I molecules to promote immune evasion. We have constructed a BHV-1 UL49.5 cytoplasmic tail (CT) null and several UL49.5 luminal domain mutants in the backbone of wild-type BHV-1 or BHV-1 UL49.5 CT- null viruses and determined their relative TAP mediated peptide transport inhibition and MHC-1 down-regulation properties compared with BHV-1 wt. Based on our results, the UL49.5 luminal domain residues 30–32 and UL49.5 CT residues, together, promote efficient TAP inhibition and MHC-I down-regulation functions. In vitro, BHV-1 UL49.5 Δ30–32 CT-null virus growth property was similar to that of BHV-1 wt and like the wt UL49.5, the mutant UL49.5 was incorporated in the virion envelope and it formed a complex with gM in the infected cells

Diffuse-reflectance spectroscopy using a frequency-switchable terahertz quantum cascade laser

We demonstrate diffuse-reflectance (DR) spectroscopy of powders using a discretely-tunable terahertz-frequency quantum cascade laser (THz QCL) with a heterogeneous active region. DR signatures were obtained at frequencies of 3.06, 3.21, 3.28 and 3.35 THz, and the relative absorption coefficients were inferred at each frequency using a Kubelka–Munk (KM) scattering model. The spectral lineshapes reproduce the absolute Beer–Lambert (BL) absorption spectra of a range of materials, which were also measured using conventional transmission-mode THz time-domain spectroscopy. It is shown that the DR technique works reliably for materials that include pharmaceutical compounds and foodstuffs, with BL absorption coefficients in the range 2–10 mm−1. This method is potentially suitable for automated material identification, without any requirement for a priori knowledge of the refractive index or scattering properties of the sampled material

DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis

Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of sufficiently large and comprehensive datasets is currently a bottleneck for the progress of DMS development, crucial for the transition of automated driving from SAE Level-2 to SAE Level-3. In this paper, we introduce the Driver Monitoring Dataset (DMD), an extensive dataset which includes real and simulated driving scenarios: distraction, gaze allocation, drowsiness, hands-wheel interaction and context data, in 41 hours of RGB, depth and IR videos from 3 cameras capturing face, body and hands of 37 drivers. A comparison with existing similar datasets is included, which shows the DMD is more extensive, diverse, and multi-purpose. The usage of the DMD is illustrated by extracting a subset of it, the dBehaviourMD dataset, containing 13 distraction activities, prepared to be used in DL training processes. Furthermore, we propose a robust and real-time driver behaviour recognition system targeting a real-world application that can run on cost-efficient CPU-only platforms, based on the dBehaviourMD. Its performance is evaluated with different types of fusion strategies, which all reach enhanced accuracy still providing real-time response.Comment: Accepted to ECCV 2020 workshop - Assistive Computer Vision and Robotic