Identifying Defects in Li-Ion Cells Using Ultrasound Acoustic Measurements

Identification of the state-of-health (SoH) of Li-ion cells is a vital tool to protect operating battery packs against accelerated degradation and failure. This is becoming increasingly important as the energy and power densities demanded by batteries and the economic costs of packs increase. Here, ultrasonic time-of-flight analysis is performed to demonstrate the technique as a tool for the identification of a range of defects and SoH in Li-ion cells. Analysis of large, purpose-built defects across multiple length scales is performed in pouch cells. The technique is then demonstrated to detect a microscale defect in a commercial cell, which is validated by examining the acoustic transmission signal through the cell. The location and scale of the defects are confirmed using X-ray computed tomography, which also provides information pertaining to the layered structure of the cells. The demonstration of this technique as a methodology for obtaining direct, non-destructive, depth-resolved measurements of the condition of electrode layers highlights the potential application of acoustic methods in real-time diagnostics for SoH monitoring and manufacturing processes

Zoonotic disease research in East Africa

Abstract Background The East African region is endemic with multiple zoonotic diseases and is one of the hotspots for emerging infectious zoonotic diseases with reported multiple outbreaks of epidemic diseases such as Ebola, Marburg and Rift Valley Fever. Here we present a systematic assessment of published research on zoonotic diseases in the region and thesis research in Kenya to understand the regional research focus and trends in publications, and estimate proportion of theses research transitioning to peer-reviewed journal publications. Methods We searched PubMed, Google Scholar and African Journals Online databases for publications on 36 zoonotic diseases identified to have occurred in the East Africa countries of Burundi, Ethiopia, Kenya, Tanzania, Rwanda and Uganda, for the period between 1920 and 2017. We searched libraries and queried online repositories for masters and PhD theses on these diseases produced between 1970 and 2016 in five universities and two research institutions in Kenya. Results We identified 771 journal articles on 22, and 168 theses on 21 of the 36 zoonotic diseases investigated. Research on zoonotic diseases increased exponentially with the last 10 years of our study period contributing more than half of all publications 460 (60%) and theses 102 (61%) retrieved. Endemic diseases were the most studied accounting for 656 (85%) and 150 (89%) of the publication and theses studies respectively, with publications on epidemic diseases associated with outbreaks reported in the region or elsewhere. Epidemiological studies were the most common study types but limited to cross-sectional studies while socio-economics were the least studied. Only 11% of the theses research transitioned to peer-review publications, taking an average of 2.5 years from theses production to manuscript publication. Conclusion Our findings demonstrate increased attention to zoonotic diseases in East Africa but reveal the need to expand the scope, focus and quality of studies to adequately address the public health, social and economic threats posed by zoonoses

Linkage map construction involving a reciprocal translocation

This paper is concerned with a novel statistical–genetic approach for the construction of linkage maps in populations obtained from reciprocal translocation heterozygotes of barley (Hordeum vulgare L.). Using standard linkage analysis, translocations usually lead to ‘pseudo-linkage’: the mixing up of markers from the chromosomes involved in the translocation into a single linkage group. Close to the translocation breakpoints recombination is severely suppressed and, as a consequence, ordering markers in those regions is not feasible. The novel strategy presented in this paper is based on (1) disentangling the “pseudo-linkage” using principal coordinate analysis, (2) separating individuals into translocated types and normal types and (3) separating markers into those close to and those more distant from the translocation breakpoints. The methods make use of a consensus map of the species involved. The final product consists of integrated linkage maps of the distal parts of the chromosomes involved in the translocation

Convergence among Non-Sister Dendritic Branches: An Activity-Controlled Mean to Strengthen Network Connectivity

The manner by which axons distribute synaptic connections along dendrites remains a fundamental unresolved issue in neuronal development and physiology. We found in vitro and in vivo indications that dendrites determine the density, location and strength of their synaptic inputs by controlling the distance of their branches from those of their neighbors. Such control occurs through collective branch convergence, a behavior promoted by AMPA and NMDA glutamate receptor activity. At hubs of convergence sites, the incidence of axo-dendritic contacts as well as clustering levels, pre- and post-synaptic protein content and secretion capacity of synaptic connections are higher than found elsewhere. This coupling between synaptic distribution and the pattern of dendritic overlapping results in ‘Economical Small World Network’, a network configuration that enables single axons to innervate multiple and remote dendrites using short wiring lengths. Thus, activity-mediated regulation of the proximity among dendritic branches serves to pattern and strengthen neuronal connectivity

Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence

Cigarette smoking is a leading cause of preventable mortality worldwide. Nicotine dependence, which reduces the likelihood of quitting smoking, is a heritable trait with firmly established associations with sequence variants in nicotine acetylcholine receptor genes and at other loci. To search for additional loci, we conducted a genome-wide association study (GWAS) meta-analysis of nicotine dependence, totaling 38,602 smokers (28,677 Europeans/European Americans and 9925 African Americans) across 15 studies. In this largest-ever GWAS meta-analysis for nicotine dependence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfirmed the well-known CHRNA5-CHRNA3-CHRNB4 genes and further yielded a novel association in the DNA methyltransferase gene DNMT3B. The intronic DNMT3B rs910083-C allele (frequency = 44-77%) was associated with increased risk of nicotine dependence at P = 3.7 x 10(-8) (odds ratio (OR) = 1.06 and 95% confidence interval (CI) = 1.04-1.07 for severe vs mild dependence). The association was independently confirmed in the UK Biobank (N = 48,931) using heavy vs never smoking as a proxy phenotype (P = 3.6 x 10(-4), OR = 1.05, and 95% CI = 1.02-1.08). Rs910083-C is also associated with increased risk of squamous cell lung carcinoma in the International Lung Cancer Consortium (N = 60,586, meta-analysis P = 0.0095, OR = 1.05, and 95% CI = 1.01-1.09). Moreover, rs910083-C was implicated as a cis-methylation quantitative trait locus (QTL) variant associated with higher DNMT3B methylation in fetal brain (N = 166, P = 2.3 x 10(-26)) and a cis-expression QTL variant associated with higher DNMT3B expression in adult cerebellum from the Genotype-Tissue Expression project (N = 103, P = 3.0 x 10(-6)) and the independent Brain eQTL Almanac (N = 134, P = 0.028). This novel DNMT3B cis-acting QTL variant highlights the importance of genetically influenced regulation in brain on the risks of nicotine dependence, heavy smoking and consequent lung cancer.Peer reviewe

Perinatal asphyxia: current status and approaches towards neuroprotective strategies, with focus on sentinel proteins

Delivery is a stressful and risky event menacing the newborn. The mother-dependent respiration has to be replaced by autonomous pulmonary breathing immediately after delivery. If delayed, it may lead to deficient oxygen supply compromising survival and development of the central nervous system. Lack of oxygen availability gives rise to depletion of NAD+ tissue stores, decrease of ATP formation, weakening of the electron transport pump and anaerobic metabolism and acidosis, leading necessarily to death if oxygenation is not promptly re-established. Re-oxygenation triggers a cascade of compensatory biochemical events to restore function, which may be accompanied by improper homeostasis and oxidative stress. Consequences may be incomplete recovery, or excess reactions that worsen the biological outcome by disturbed metabolism and/or imbalance produced by over-expression of alternative metabolic pathways. Perinatal asphyxia has been associated with severe neurological and psychiatric sequelae with delayed clinical onset. No specific treatments have yet been established. In the clinical setting, after resuscitation of an infant with birth asphyxia, the emphasis is on supportive therapy. Several interventions have been proposed to attenuate secondary neuronal injuries elicited by asphyxia, including hypothermia. Although promising, the clinical efficacy of hypothermia has not been fully demonstrated. It is evident that new approaches are warranted. The purpose of this review is to discuss the concept of sentinel proteins as targets for neuroprotection. Several sentinel proteins have been described to protect the integrity of the genome (e.g. PARP-1; XRCC1; DNA ligase IIIα; DNA polymerase β, ERCC2, DNA-dependent protein kinases). They act by eliciting metabolic cascades leading to (i) activation of cell survival and neurotrophic pathways; (ii) early and delayed programmed cell death, and (iii) promotion of cell proliferation, differentiation, neuritogenesis and synaptogenesis. It is proposed that sentinel proteins can be used as markers for characterising long-term effects of perinatal asphyxia, and as targets for novel therapeutic development and innovative strategies for neonatal care

Automated Adaptation Strategies for Stream Learning

Automation of machine learning model development is increasingly becoming an established research area. While automated model selection and automated data pre-processing have been studied in depth, there is, however, a gap concerning automated model adaptation strategies when multiple strategies are available. Manually developing an adaptation strategy can be time consuming and costly. In this paper we address this issue by proposing the use of flexible adaptive mechanism deployment for automated development of adaptation strategies. Experimental results after using the proposed strategies with five adaptive algorithms on 36 datasets confirm their viability. These strategies achieve better or comparable performance to the custom adaptation strategies and the repeated deployment of any single adaptive mechanism

Deconvolution of complex G protein–coupled receptor signaling in live cells using dynamic mass redistribution measurements

Label-free biosensor technology based on dynamic mass redistribution (DMR) of cellular constituents promises to translate GPCR signaling into complex optical 'fingerprints' in real time in living cells. Here we present a strategy to map cellular mechanisms that define label-free responses, and we compare DMR technology with traditional second-messenger assays that are currently the state of the art in GPCR drug discovery. The holistic nature of DMR measurements enabled us to (i) probe GPCR functionality along all four G-protein signaling pathways, something presently beyond reach of most other assay platforms; (ii) dissect complex GPCR signaling patterns even in primary human cells with unprecedented accuracy; (iii) define heterotrimeric G proteins as triggers for the complex optical fingerprints; and (iv) disclose previously undetected features of GPCR behavior. Our results suggest that DMR technology will have a substantial impact on systems biology and systems pharmacology as well as for the discovery of drugs with novel mechanisms

Genome-wide association study of primary sclerosing cholangitis identifies new risk loci and quantifies the genetic relationship with inflammatory bowel disease.

Primary sclerosing cholangitis (PSC) is a rare progressive disorder leading to bile duct destruction; ∼75% of patients have comorbid inflammatory bowel disease (IBD). We undertook the largest genome-wide association study of PSC (4,796 cases and 19,955 population controls) and identified four new genome-wide significant loci. The most associated SNP at one locus affects splicing and expression of UBASH3A, with the protective allele (C) predicted to cause nonstop-mediated mRNA decay and lower expression of UBASH3A. Further analyses based on common variants suggested that the genome-wide genetic correlation (rG) between PSC and ulcerative colitis (UC) (rG = 0.29) was significantly greater than that between PSC and Crohn's disease (CD) (rG = 0.04) (P = 2.55 × 10-15). UC and CD were genetically more similar to each other (rG = 0.56) than either was to PSC (P < 1.0 × 10-15). Our study represents a substantial advance in understanding of the genetics of PSC