Z-Spectral Modeling for Magnetization Transfer Ratio Asymmetry Calculations in Chemical Exchange Saturation Transfer MRI at 3 Tesla

Chemical exchange saturation transfer (CEST) and magnetization transfer (MT) are types of magnetic resonance imaging (MRI) experiments in which contrast is based on the transfer of magnetization from selectively saturated solute or macromolecular protons to bulk water protons. These processes offer insight into the chemical composition of tissue and are quantified by the asymmetry of the magnetization transfer ratio (MTRasym). This study was to develop a Z-spectral curve fitting procedure based on the underlying physics of CEST-MRI from which MTRasym values can be calculated and applied to distinguish healthy tissue from cancer. Z-spectra were collected from CEST-MR images of a phantom. The data were fit to both the proposed model which separately fits the upfield and downfield regions of the Z-spectra, and two polynomial models from literature. A preferred model was identified using the small sample bias-corrected Akaike’s Information Criterion (AICc). Z-spectra were collected from CEST-MR images of prostate cancer patients and fit with the same models; the preferred model was selected using the AICc. CEST-MR images of bladder cancer patients were acquired and the Z-spectra were fit with the preferred model identified from the phantom images. MTRasym was calculated at frequency offsets of 3.5 ppm and 2.0 ppm to determine if these quantities were capable of distinguishing normal bladder wall (NBW) from bladder cancer. The proposed fitting model with a 5th order polynomial for the downfield region was the preferred curve fitting model by the AICc model selection procedure for the phantom while a 6th order polynomial was preferred for the prostate cancer Z-spectra. MTRasym(2.0 ppm) values calculated from the bladder cancer Z-spectra did not differ significantly between the NBW and tumor regions. A statistically significant difference existed between the NBW and tumor regions for the MTRasym(3.5 ppm) values (p \u3c 0.001). The proposed model was preferred to the polynomial models from literature based on the AICc metric. Application of the technique to patient images showed the potential to distinguish NBW from bladder cancer based on the statistically significant MTRasym(3.5 ppm) values in these regions

Hello World! I am Charlie, an Artificially Intelligent Conference Panelist

In recent years, advances in artificial intelligence (AI) have far outpaced our ability to understand and leverage them. In no domain has this been more true than in conversational agents (CAs). Transformer-based generative language models, such as GPT-2, significantly advance CAs\u27 ability to generate creative and relevant content. It is critical to start exploring collaboration with these CAs. In this paper, we focus on an initial step by enabling a human-augmented, AI-driven CA to contribute to a panel discussion. Key questions include training a transformer-based AI to talk like a panelist, effectively embodying the CA to interact with panel participants, and defining the operational requirements and challenges to a CA gaining acceptance from its peers. Our results highlight the benefits that varied training, equal and dynamic representation, and fluid operation can have for AI applications. While acknowledging limitations, we present a path forward to richer, more natural human-AI collaboration

Practice Makes Perfect: Lesson Learned from Five Years of Trial and Error Building Context-Aware Systems

Recent advances in artificial intelligence have demonstrated that the future of work will be defined by collaborative human-machine teams. In order to be effective, human-machine teams will rely on context-aware systems to enable collaboration. In this paper, we present three lessons learned from the past five years of developing context-aware systems that we believe will improve future system design. First, that semantic activity must captured, modeled, and analyzed to enable reasoning across missions, actors, and content. Second, that context-aware systems require multiple, federated data stores to optimize system and team performance. Finally, that real-time inter-actor communications are the essential feature enabling adaptation. We close with a discussion of the influences and implications that these lessons have on human-machine teaming, and outline future research activities that will be necessary before operationalizing these systems

Expression of mucoid induction factor MucE is dependent upon the alternate sigma factor AlgU in Pseudomonas aeruginosa

Background Alginate overproduction in P. aeruginosa, also referred to as mucoidy, is a poor prognostic marker for patients with cystic fibrosis (CF). We previously reported the construction of a unique mucoid strain which overexpresses a small envelope protein MucE leading to activation of the protease AlgW. AlgW then degrades the anti-sigma factor MucA thus releasing the alternative sigma factor AlgU/T (σ22) to initiate transcription of the alginate biosynthetic operon. Results In the current study, we mapped the mucE transcriptional start site, and determined that PmucE activity was dependent on AlgU. Additionally, the presence of triclosan and sodium dodecyl sulfate was shown to cause an increase in PmucE activity. It was observed that mucE-mediated mucoidy in CF isolates was dependent on both the size of MucA and the genotype of algU. We also performed shotgun proteomic analysis with cell lysates from the strains PAO1, VE2 (PAO1 with constitutive expression of mucE) and VE2ΔalgU (VE2 with in-frame deletion of algU). As a result, we identified nine algU-dependent and two algU-independent proteins that were affected by overexpression of MucE. Conclusions Our data indicates there is a positive feedback regulation between MucE and AlgU. Furthermore, it seems likely that MucE may be part of the signal transduction system that senses certain types of cell wall stress to P. aeruginosa

Phosphatase-mediated bioprecipitation of lead by soil fungi

Geoactive soil fungi were examined for their ability to release inorganic phosphate (Pi ) and mediate lead bioprecipitation during growth on organic phosphate substrates. Aspergillus niger and Paecilomyces javanicus grew in 5 mM Pb(NO3 )2 -containing media amended with glycerol 2-phosphate (G2P) or phytic acid (PyA) as sole P sources, and liberated Pi into the medium. This resulted in almost complete removal of Pb from solution and extensive precipitation of lead-containing minerals around the biomass, confirming the importance of the mycelium as a reactive network for biomineralization. The minerals were identified as pyromorphite (Pb5 (PO4 )3 Cl), only produced by P. javanicus, and lead oxalate (PbC2 O4 ), produced by A. niger and P. javanicus. Geochemical modelling of lead and lead mineral speciation as a function of pH and oxalate closely correlated with experimental conditions and data. Two main lead biomineralization mechanisms were therefore distinguished: pyromorphite formation depending on organic phosphate hydrolysis and lead oxalate formation depending on oxalate excretion. This also indicated species specificity in biomineralization depending on nutrition and physiology. Our findings provide further understanding of lead geomycology and organic phosphates as a biomineralization substrate, and are also relevant to metal immobilization biotechnologies for bioremediation, metal and P biorecovery, and utilization of waste organic phosphates

Mitochondrial Lactate Dehydrogenase Is Involved in Oxidative-Energy Metabolism in Human Astrocytoma Cells (CCF-STTG1)

Lactate has long been regarded as an end product of anaerobic energy production and its fate in cerebral metabolism has not been precisely delineated. In this report, we demonstrate, for the first time, the ability of a human astrocytic cell line (CCF-STTG1) to consume lactate and to generate ATP via oxidative phosphorylation. 13C-NMR and HPLC analyses aided in the identification of tricarboxylic acid (TCA) cyle metabolites and ATP in the astrocytic mitochondria incubated with lactate. Oxamate, an inhibitor of lactate dehydrogenase (LDH), abolished mitochondrial lactate consumption. Electrophoretic and fluorescence microscopic analyses helped localize LDH in the mitochondria. Taken together, this study implicates lactate as an important contributor to ATP metabolism in the brain, a finding that may significantly change our notion of how this important organ manipulates its energy budget

LRRK2 Biology from structure to dysfunction: research progresses, but the themes remain the same

Since the discovery of leucine-rich repeat kinase 2 (LRRK2) as a protein that is likely central to the aetiology of Parkinson's disease, a considerable amount of work has gone into uncovering its basic cellular function. This effort has led to the implication of LRRK2 in a bewildering range of cell biological processes and pathways, and probable roles in a number of seemingly unrelated medical conditions. In this review we summarise current knowledge of the basic biochemistry and cellular function of LRRK2. Topics covered include the identification of phosphorylation substrates of LRRK2 kinase activity, in particular Rab proteins, and advances in understanding the activation of LRRK2 kinase activity via dimerisation and association with membranes, especially via interaction with Rab29. We also discuss biochemical studies that shed light on the complex LRRK2 GTPase activity, evidence of roles for LRRK2 in a range of cell signalling pathways that are likely cell type specific, and studies linking LRRK2 to the cell biology of organelles. The latter includes the involvement of LRRK2 in autophagy, endocytosis, and processes at the trans-Golgi network, the endoplasmic reticulum and also key microtubule-based cellular structures. We further propose a mechanism linking LRRK2 dimerisation, GTPase function and membrane recruitment with LRRK2 kinase activation by Rab29. Together these data paint a picture of a research field that in many ways is moving forward with great momentum, but in other ways has not changed fundamentally. Many key advances have been made, but very often they seem to lead back to the same places

Treat me well and I may leave you kindly: A configurational approach to a buyer’s relationship exit strategy

Research shows that the choice of relationship exit strategy by the instigator of exit can have significant negative consequences for the party that is being dropped. In this study we focus on what we coin as kind exit, where the risk of harm to the supplier as a result of the buyer’s relationship termination is low. In line with current research, which is suggesting that the characteristics of a buyer-supplier relationship play a critical role in the instigator’s choice of exit strategy, we examine the link between the buyer’s perception of its relationship with the supplier and the manner in which the buyer-supplier relationship ends. We posit that this phenomenon is causally complex and context dependent, and as such, there will be multiple types of buyer-supplier relationships that will lead to a kind exit. To uncover these types, we examine 315 terminated buyer-supplier relationships in manufacturing and service sectors in the UK, employing fuzzy set qualitative comparative analysis (fsQCA). Our results show that contrary to extant literature, there is not one relationship type that leads to a kind exit; instead, we uncover four alternative equifinal configurations of relationship dimensions and two exogenous factors

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe