Spontaneous spatial fractals: universal contexts and applications

We report on our latest research in the field of spontaneous spatial fractal patterns. New analyses, results and potential applications are reported for nonlinear ring cavities and kaleidoscope laser systems

FKBPL is associated with metabolic parameters and is a novel determinant of cardiovascular disease.

Type 2 diabetes (T2D) is associated with increased risk of cardiovascular disease (CVD). As disturbed angiogenesis and endothelial dysfunction are strongly implicated in T2D and CVD, we aimed to investigate the association between a novel anti-angiogenic protein, FK506-binding protein like (FKBPL), and these diseases. Plasma FKBPL was quantified by ELISA cross-sectionally in 353 adults, consisting of 234 T2D and 119 non-diabetic subjects with/without CVD, matched for age, BMI and gender. FKBPL levels were higher in T2D (adjusted mean: 2.03 ng/ml ± 0.90 SD) vs. non-diabetic subjects (adjusted mean: 1.79 ng/ml ± 0.89 SD, p = 0.02), but only after adjustment for CVD status. In T2D, FKBPL was negatively correlated with fasting blood glucose, HbA1c and diastolic blood pressure (DBP), and positively correlated with age, known diabetes duration, waist/hip ratio, urinary albumin/creatinine ratio (ACR) and fasting C-peptide. FKBPL plasma concentrations were increased in the presence of CVD, but only in the non-diabetic group (CVD: 2.02 ng/ml ± 0.75 SD vs. no CVD: 1.68 ng/ml ± 0.79 SD, p = 0.02). In non-diabetic subjects, FKBPL was positively correlated with an established biomarker for CVD, B-type Natriuretic Peptide (BNP), and echocardiographic parameters of diastolic dysfunction. FKBPL was a determinant of CVD in the non-diabetic group in addition to age, gender, total-cholesterol and systolic blood pressure (SBP). FKBPL may be a useful anti-angiogenic biomarker in CVD in the absence of diabetes and could represent a novel CVD mechanism

Measurement of 222Rn dissolved in water at the Sudbury Neutrino Observatory

The technique used at the Sudbury Neutrino Observatory (SNO) to measure the concentration of 222Rn in water is described. Water from the SNO detector is passed through a vacuum degasser (in the light water system) or a membrane contact degasser (in the heavy water system) where dissolved gases, including radon, are liberated. The degasser is connected to a vacuum system which collects the radon on a cold trap and removes most other gases, such as water vapor and nitrogen. After roughly 0.5 tonnes of H2O or 6 tonnes of D2O have been sampled, the accumulated radon is transferred to a Lucas cell. The cell is mounted on a photomultiplier tube which detects the alpha particles from the decay of 222Rn and its daughters. The overall degassing and concentration efficiency is about 38% and the single-alpha counting efficiency is approximately 75%. The sensitivity of the radon assay system for D2O is equivalent to ~3 E(-15) g U/g water. The radon concentration in both the H2O and D2O is sufficiently low that the rate of background events from U-chain elements is a small fraction of the interaction rate of solar neutrinos by the neutral current reaction.Comment: 14 pages, 6 figures; v2 has very minor change

A neurogenetic model for the study of schizophrenia spectrum disorders: The International 22q11.2 Deletion Syndrome Brain Behavior Consortium

Rare copy number variants contribute significantly to the risk for schizophrenia, with the 22q11.2 locus consistently implicated. Individuals with the 22q11.2 deletion syndrome (22q11DS) have an estimated 25-fold increased risk for schizophrenia spectrum disorders, compared to individuals in the general population. The International 22q11DS Brain Behavior Consortium is examining this highly informative neurogenetic syndrome phenotypically and genomically. Here we detail the procedures of the effort to characterize the neuropsychiatric and neurobehavioral phenotypes associated with 22q11DS, focusing on schizophrenia and subthreshold expression of psychosis. The genomic approach includes a combination of whole genome sequencing and genome-wide microarray technologies, allowing the investigation of all possible DNA variation and gene pathways influencing the schizophrenia-relevant phenotypic expression. A phenotypically rich data set provides a psychiatrically well-characterized sample of unprecedented size (n=1,616) that informs the neurobehavioral developmental course of 22q11DS. This combined set of phenotypic and genomic data will enable hypothesis testing to elucidate the mechanisms underlying the pathogenesis of schizophrenia spectrum disorders

3-D Ultrastructure of O. tauri: Electron Cryotomography of an Entire Eukaryotic Cell

The hallmark of eukaryotic cells is their segregation of key biological functions into discrete, membrane-bound organelles. Creating accurate models of their ultrastructural complexity has been difficult in part because of the limited resolution of light microscopy and the artifact-prone nature of conventional electron microscopy. Here we explored the potential of the emerging technology electron cryotomography to produce three-dimensional images of an entire eukaryotic cell in a near-native state. Ostreococcus tauri was chosen as the specimen because as a unicellular picoplankton with just one copy of each organelle, it is the smallest known eukaryote and was therefore likely to yield the highest resolution images. Whole cells were imaged at various stages of the cell cycle, yielding 3-D reconstructions of complete chloroplasts, mitochondria, endoplasmic reticula, Golgi bodies, peroxisomes, microtubules, and putative ribosome distributions in-situ. Surprisingly, the nucleus was seen to open long before mitosis, and while one microtubule (or two in some predivisional cells) was consistently present, no mitotic spindle was ever observed, prompting speculation that a single microtubule might be sufficient to segregate multiple chromosomes

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

Neutrophil swarming and extracellular trap formation play a significant role in Alum adjuvant activity

There are over 6 billion vaccine doses administered each year, most containing aluminium-based adjuvants, yet we still do not have a complete understanding of their mechanisms of action. Recent evidence has identified host DNA and downstream sensing as playing a significant role in aluminium adjuvant (aluminium hydroxide) activity. However, the cellular source of this DNA, how it is sensed by the immune system and the consequences of this for vaccination remains unclear. Here we show that the very early injection site reaction is characterised by inflammatory chemokine production and neutrophil recruitment. Intravital imaging demonstrates that the Alum injection site is a focus of neutrophil swarms and extracellular DNA strands. These strands were confirmed as neutrophil extracellular traps due to their sensitivity to DNAse and absence in mice deficient in peptidylarginine deiminase 4. Further studies in PAD4−/− mice confirmed a significant role for neutrophil extracellular trap formation in the adjuvant activity of Alum. By revealing neutrophils recruited to the site of Alum injection as a source of the DNA that is detected by the immune system this study provides the missing link between Alum injection and the activation of DNA sensors that enhance adjuvant activity, elucidating a key mechanism of action for this important vaccine component