Bi-allelic JAM2 Variants Lead to Early-Onset Recessive Primary Familial Brain Calcification.

Primary familial brain calcification (PFBC) is a rare neurodegenerative disorder characterized by a combination of neurological, psychiatric, and cognitive decline associated with calcium deposition on brain imaging. To date, mutations in five genes have been linked to PFBC. However, more than 50% of individuals affected by PFBC have no molecular diagnosis. We report four unrelated families presenting with initial learning difficulties and seizures and later psychiatric symptoms, cerebellar ataxia, extrapyramidal signs, and extensive calcifications on brain imaging. Through a combination of homozygosity mapping and exome sequencing, we mapped this phenotype to chromosome 21q21.3 and identified bi-allelic variants in JAM2. JAM2 encodes for the junctional-adhesion-molecule-2, a key tight-junction protein in blood-brain-barrier permeability. We show that JAM2 variants lead to reduction of JAM2 mRNA expression and absence of JAM2 protein in patient's fibroblasts, consistent with a loss-of-function mechanism. We show that the human phenotype is replicated in the jam2 complete knockout mouse (jam2 KO). Furthermore, neuropathology of jam2 KO mouse showed prominent vacuolation in the cerebral cortex, thalamus, and cerebellum and particularly widespread vacuolation in the midbrain with reactive astrogliosis and neuronal density reduction. The regions of the human brain affected on neuroimaging are similar to the affected brain areas in the myorg PFBC null mouse. Along with JAM3 and OCLN, JAM2 is the third tight-junction gene in which bi-allelic variants are associated with brain calcification, suggesting that defective cell-to-cell adhesion and dysfunction of the movement of solutes through the paracellular spaces in the neurovascular unit is a key mechanism in CNS calcification

Quiet in class: classification, noise and the dendritic cell algorithm

Theoretical analyses of the Dendritic Cell Algorithm (DCA) have yielded several criticisms about its underlying structure and operation. As a result, several alterations and fixes have been suggested in the literature to correct for these findings. A contribution of this work is to investigate the effects of replacing the classification stage of the DCA (which is known to be flawed) with a traditional machine learning technique. This work goes on to question the merits of those unique properties of the DCA that are yet to be thoroughly analysed. If none of these properties can be found to have a benefit over traditional approaches, then “fixing” the DCA is arguably less efficient than simply creating a new algorithm. This work examines the dynamic filtering property of the DCA and questions the utility of this unique feature for the anomaly detection problem. It is found that this feature, while advantageous for noisy, time-ordered classification, is not as useful as a traditional static filter for processing a synthetic dataset. It is concluded that there are still unique features of the DCA left to investigate. Areas that may be of benefit to the Artificial Immune Systems community are suggested

The Impact of Global Warming and Anoxia on Marine Benthic Community Dynamics: an Example from the Toarcian (Early Jurassic)

The Pliensbachian-Toarcian (Early Jurassic) fossil record is an archive of natural data of benthic community response to global warming and marine long-term hypoxia and anoxia. In the early Toarcian mean temperatures increased by the same order of magnitude as that predicted for the near future; laminated, organic-rich, black shales were deposited in many shallow water epicontinental basins; and a biotic crisis occurred in the marine realm, with the extinction of approximately 5% of families and 26% of genera. High-resolution quantitative abundance data of benthic invertebrates were collected from the Cleveland Basin (North Yorkshire, UK), and analysed with multivariate statistical methods to detect how the fauna responded to environmental changes during the early Toarcian. Twelve biofacies were identified. Their changes through time closely resemble the pattern of faunal degradation and recovery observed in modern habitats affected by anoxia. All four successional stages of community structure recorded in modern studies are recognised in the fossil data (i.e. Stage III: climax; II: transitional; I: pioneer; 0: highly disturbed). Two main faunal turnover events occurred: (i) at the onset of anoxia, with the extinction of most benthic species and the survival of a few adapted to thrive in low-oxygen conditions (Stages I to 0) and (ii) in the recovery, when newly evolved species colonized the re-oxygenated soft sediments and the path of recovery did not retrace of pattern of ecological degradation (Stages I to II). The ordination of samples coupled with sedimentological and palaeotemperature proxy data indicate that the onset of anoxia and the extinction horizon coincide with both a rise in temperature and sea level. Our study of how faunal associations co-vary with long and short term sea level and temperature changes has implications for predicting the long-term effects of “dead zones” in modern oceans

Examination of the Effects of Heterogeneous Organization of RyR Clusters, Myofibrils and Mitochondria on Ca2+ Release Patterns in Cardiomyocytes

Spatio-temporal dynamics of intracellular calcium, [Ca2+]i, regulate the contractile function of cardiac muscle cells. Measuring [Ca2+]i flux is central to the study of mechanisms that underlie both normal cardiac function and calcium-dependent etiologies in heart disease. However, current imaging techniques are limited in the spatial resolution to which changes in [Ca2+]i can be detected. Using spatial point process statistics techniques we developed a novel method to simulate the spatial distribution of RyR clusters, which act as the major mediators of contractile Ca2+ release, upon a physiologically-realistic cellular landscape composed of tightly-packed mitochondria and myofibrils.We applied this method to computationally combine confocal-scale (~ 200 nm) data of RyR clusters with 3D electron microscopy data (~ 30 nm) of myofibrils and mitochondria, both collected from adult rat left ventricular myocytes. Using this hybrid-scale spatial model, we simulated reaction-diffusion of [Ca2+]i during the rising phase of the transient (first 30 ms after initiation). At 30 ms, the average peak of the simulated [Ca2+]i transient and of the simulated fluorescence intensity signal, F/F0, reached values similar to that found in the literature ([Ca2+]i 1 μM; F/F0 5.5). However, our model predicted the variation in [Ca2+]i to be between 0.3 and 12.7 μM (~3 to 100 fold from resting value of 0.1 μM) and the corresponding F/F0 signal ranging from 3 to 9.5. We demonstrate in this study that: (i) heterogeneities in the [Ca2+]i transient are due not only to heterogeneous distribution and clustering of mitochondria; (ii) but also to heterogeneous local densities of RyR clusters. Further, we show that: (iii) these structureinduced heterogeneities in [Ca2+]i can appear in line scan data. Finally, using our unique method for generating RyR cluster distributions, we demonstrate the robustness in the [Ca2+]i transient to differences in RyR cluster distributions measured between rat and human cardiomyocytes

Towards Model-Based Reinforcement Learning for Industry-Near Environments

Author's accepted manuscript.Deep reinforcement learning has over the past few years shown great potential in learning near-optimal control in complex simulated environments with little visible information. Rainbow (Q-Learning) and PPO (Policy Optimisation) have shown outstanding performance in a variety of tasks, including Atari 2600, MuJoCo, and Roboschool test suite. Although these algorithms are fundamentally different, both suffer from high variance, low sample efficiency, and hyperparameter sensitivity that, in practice, make these algorithms a no-go for critical operations in the industry. On the other hand, model-based reinforcement learning focuses on learning the transition dynamics between states in an environment. If the environment dynamics are adequately learned, a model-based approach is perhaps the most sample efficient method for learning agents to act in an environment optimally. The traits of model-based reinforcement are ideal for real-world environments where sampling is slow and in mission-critical operations. In the warehouse industry, there is an increasing motivation to minimise time and to maximise production. In many of these environments, the literature suggests that the autonomous agents in these environments act suboptimally using handcrafted policies for a significant portion of the state-space. In this paper, we present The Dreaming Variational Autoencoder v2 (DVAE-2), a model-based reinforcement learning algorithm that increases sample efficiency, hence enable algorithms with low sample efficiency function better in real-world environments. We introduce the Deep Warehouse environment for industry-near testing of autonomous agents in logistic warehouses. We illustrate that the DVAE-2 algorithm improves the sample efficiency for the Deep Warehouse compared to model-free methods.acceptedVersio

Circulating miR-181 is a prognostic biomarker for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a relentless neurodegenerative disease of the human motor neuron system, where variability in progression rate limits clinical trial efficacy. Therefore, better prognostication will facilitate therapeutic progress. In this study, we investigated the potential of plasma cell-free microRNAs (miRNAs) as ALS prognostication biomarkers in 252 patients with detailed clinical phenotyping. First, we identified, in a longitudinal cohort, miRNAs whose plasma levels remain stable over the course of disease. Next, we showed that high levels of miR-181, a miRNA enriched in neurons, predicts a greater than two-fold risk of death in independent discovery and replication cohorts (126 and 122 patients, respectively). miR-181 performance is similar to neurofilament light chain (NfL), and when combined together, miR-181 + NfL establish a novel RNA–protein biomarker pair with superior prognostication capacity. Therefore, plasma miR-181 alone and a novel miRNA–protein biomarker approach, based on miR-181 + NfL, boost precision of patient stratification. miR-181-based ALS biomarkers encourage additional validation and might enhance the power of clinical trials

Injuries in Quidditch:A Prospective Study from a Complete UK Season

Background : Quidditch is a mixed-gender, full-contact sport founded in the USA in 2005, played worldwide by an estimated 25,000 players. It is one of the few mixed-gender full-contact sports, yet there remain few published studies regarding injury rates and patterns. A previous study suggested that the overall rate of injury in quidditch is in line with other contact sports, however raised concerns that female players were sustaining a higher rate of concussion when compared to male players. Purpose : To examine injury rates and injury patterns in UK quidditch athletes over the course of a single season. Study design: Prospective epidemiological study. Methods : Data were prospectively collected by professional first aid staff for the 2017-18 season spanning all major UK tournaments, involving 699 athletes. Anonymized player demographics were collected by an online survey. Time loss injury rates were measured per 1000 athletic exposures (AEs) and hours of play. Results: The overall time loss injury rate was 20.5 per 1000 hours or 8.0 per 1000 AEs. The combined rate of concussion was 7.3 per 1000 hours or 2.8 per 1000 AEs. There was no statistical difference between time loss injuries in males (20.9/1000 hours and 8.1/1000 AEs) and females (13.9/1000 hours and 5.4/1000 AEs) (p=0.30) and no statistical difference between concussion rates in males (n=7) and females (n=4) (p=0.60). Conclusions : Total time loss injury rates in quidditch appear to be comparable with other full-contact sports such as football. The rate of concussions for both males and females appear higher when compared to other contact sports. Level of evidence : 3Publisher PDFPeer reviewe

Ageing Contributes to Phenotype Transition in a Mouse Model of Periodic Paralysis

Background: Periodic paralysis (PP) is a rare genetic disorder in which ion channel mutation causes episodic paralysis in association with hyper- or hypokalaemia. An unexplained but consistent feature of PP is that a phenotype transition occurs around the age of 40, in which the severity of potassium-induced muscle weakness declines but onset of fixed, progressive weakness is reported. This phenotype transition coincides with the age at which muscle mass and optimal motor function start to decline in healthy individuals. We sought to determine if the phenotype transition in PP is linked to the normal ageing phenotype transition and to explore the mechanisms involved. Methods: A mouse model of hyperkalaemic PP was compared with wild-type littermates across a range of ages (13–104 weeks). Only male mice were used as penetrance is incomplete in females. We adapted the muscle velocity recovery cycle technique from humans to examine murine muscle excitability in vivo. We then examined changes in potassium-induced weakness or caffeine contracture force with age using ex vivo muscle tension testing. Muscles were further characterized by either Western blot, histology or energy charge measurement. For normally distributed data, a student's t-test (± Welch correction) or one- or two-way analysis of variance (ANOVA) was performed to determine significance. For data that were not normally distributed, Welch rank test, Mann Whitney U test or Kruskal–Wallis ANOVA was performed. When an ANOVA was significant (P < 0.05), post hoc Tukey testing was used. Results: Both WT (P = 0.009) and PP (P = 0.007) muscles exhibit increased resistance to potassium-induced weakness with age. Our data suggest that healthy-old muscle develops mechanisms to maintain force despite sarcolemmal depolarization and sodium channel inactivation. In contrast, reduced caffeine contracture force (P = 0.00005), skeletal muscle energy charge (P = 0.004) and structural core pathology (P = 0.005) were specific to Draggen muscle, indicating that they are caused, or at least accelerated by, chronic genetic ion channel dysfunction. Conclusions: The phenotype transition with age is replicated in a mouse model of PP. Intrinsic muscle ageing protects against potassium-induced weakness in HyperPP mice. However, it also appears to accelerate impairment of sarcoplasmic reticulum calcium release, mitochondrial impairment and the development of core-like regions, suggesting acquired RyR1 dysfunction as the potential aetiology. This work provides a first description of mechanisms involved in phenotype transition with age in PP. It also demonstrates how studying phenotype transition with age in monogenic disease can yield novel insights into both disease physiology and the ageing process itself