The core phageome and its interrelationship with preterm human milk lipids

\ua9 2023 The AuthorsPhages and lipids in human milk (HM) may benefit preterm infant health by preventing gastrointestinal pathobiont overgrowth and microbiome modulation. Lipid association may promote vertical transmission of phages to the infant. Despite this, interrelationships between lipids and phages are poorly characterized in preterm HM. Shotgun metagenomics and untargeted lipidomics of phage and lipid profiles from 99 preterm HM samples reveals that phages are abundant and prevalent from the first week and throughout the first 100 days of lactation. Phage-host richness of preterm HM increases longitudinally. Core phage communities characterized by Staphylococcus- and Propionibacterium-infecting phages are significantly correlated with long-chain fatty acid abundances over lactational age. We report here a phage-lipid interaction in preterm HM, highlighting the potential importance of phage carriage in preterm HM. These results reveal possible strategies for phage carriage in HM and their importance in early-life microbiota development

Beyond element-wise interactions: identifying complex interactions in biological processes

Background: Biological processes typically involve the interactions of a number of elements (genes, cells) acting on each others. Such processes are often modelled as networks whose nodes are the elements in question and edges pairwise relations between them (transcription, inhibition). But more often than not, elements actually work cooperatively or competitively to achieve a task. Or an element can act on the interaction between two others, as in the case of an enzyme controlling a reaction rate. We call “complex” these types of interaction and propose ways to identify them from time-series observations. Methodology: We use Granger Causality, a measure of the interaction between two signals, to characterize the influence of an enzyme on a reaction rate. We extend its traditional formulation to the case of multi-dimensional signals in order to capture group interactions, and not only element interactions. Our method is extensively tested on simulated data and applied to three biological datasets: microarray data of the Saccharomyces cerevisiae yeast, local field potential recordings of two brain areas and a metabolic reaction. Conclusions: Our results demonstrate that complex Granger causality can reveal new types of relation between signals and is particularly suited to biological data. Our approach raises some fundamental issues of the systems biology approach since finding all complex causalities (interactions) is an NP hard problem

Development of an international standard set of outcome measures for patients with atrial fibrillation: a report of the International Consortium for Health Outcomes Measurement (ICHOM) atrial fibrillation working group.

AIMS: As health systems around the world increasingly look to measure and improve the value of care that they provide to patients, being able to measure the outcomes that matter most to patients is vital. To support the shift towards value-based health care in atrial fibrillation (AF), the International Consortium for Health Outcomes Measurement (ICHOM) assembled an international Working Group (WG) of 30 volunteers, including health professionals and patient representatives to develop a standardized minimum set of outcomes for benchmarking care delivery in clinical settings. METHODS AND RESULTS: Using an online-modified Delphi process, outcomes important to patients and health professionals were selected and categorized into (i) long-term consequences of disease outcomes, (ii) complications of treatment outcomes, and (iii) patient-reported outcomes. The WG identified demographic and clinical variables for use as case-mix risk adjusters. These included baseline demographics, comorbidities, cognitive function, date of diagnosis, disease duration, medications prescribed and AF procedures, as well as smoking, body mass index (BMI), alcohol intake, and physical activity. Where appropriate, and for ease of implementation, standardization of outcomes and case-mix variables was achieved using ICD codes. The standard set underwent an open review process in which over 80% of patients surveyed agreed with the outcomes captured by the standard set. CONCLUSION: Implementation of these consensus recommendations could help institutions to monitor, compare and improve the quality and delivery of chronic AF care. Their consistent definition and collection, using ICD codes where applicable, could also broaden the implementation of more patient-centric clinical outcomes research in AF

Attention-dependent modulation of cortical taste circuits revealed by granger causality with signal-dependent noise

We show, for the first time, that in cortical areas, for example the insular, orbitofrontal, and lateral prefrontal cortex, there is signal-dependent noise in the fMRI blood-oxygen level dependent (BOLD) time series, with the variance of the noise increasing approximately linearly with the square of the signal. Classical Granger causal models are based on autoregressive models with time invariant covariance structure, and thus do not take this signal-dependent noise into account. To address this limitation, here we describe a Granger causal model with signal-dependent noise, and a novel, likelihood ratio test for causal inferences. We apply this approach to the data from an fMRI study to investigate the source of the top-down attentional control of taste intensity and taste pleasantness processing. The Granger causality with signal-dependent noise analysis reveals effects not identified by classical Granger causal analysis. In particular, there is a top-down effect from the posterior lateral prefrontal cortex to the insular taste cortex during attention to intensity but not to pleasantness, and there is a top-down effect from the anterior and posterior lateral prefrontal cortex to the orbitofrontal cortex during attention to pleasantness but not to intensity. In addition, there is stronger forward effective connectivity from the insular taste cortex to the orbitofrontal cortex during attention to pleasantness than during attention to intensity. These findings indicate the importance of explicitly modeling signal-dependent noise in functional neuroimaging, and reveal some of the processes involved in a biased activation theory of selective attention

Assessing genetic polymorphisms using DNA extracted from cells present in saliva samples

<p>Abstract</p> <p>Background</p> <p>Technical advances following the Human Genome Project revealed that high-quality and -quantity DNA may be obtained from whole saliva samples. However, usability of previously collected samples and the effects of environmental conditions on the samples during collection have not been assessed in detail. In five studies we document the effects of sample volume, handling and storage conditions, type of collection device, and oral sampling location, on quantity, quality, and genetic assessment of DNA extracted from cells present in saliva.</p> <p>Methods</p> <p>Saliva samples were collected from ten adults in each study. Saliva volumes from .10-1.0 ml, different saliva collection devices, sampling locations in the mouth, room temperature storage, and multiple freeze-thaw cycles were tested. One representative single nucleotide polymorphism (SNP) in the catechol-<it>0</it>-methyltransferase gene (COMT rs4680) and one representative variable number of tandem repeats (VNTR) in the serotonin transporter gene (5-HTTLPR: serotonin transporter linked polymorphic region) were selected for genetic analyses.</p> <p>Results</p> <p>The smallest tested whole saliva volume of .10 ml yielded, on average, 1.43 ± .77 μg DNA and gave accurate genotype calls in both genetic analyses. The usage of collection devices reduced the amount of DNA extracted from the saliva filtrates compared to the whole saliva sample, as 54-92% of the DNA was retained on the device. An "adhered cell" extraction enabled recovery of this DNA and provided good quality and quantity DNA. The DNA from both the saliva filtrates and the adhered cell recovery provided accurate genotype calls. The effects of storage at room temperature (up to 5 days), repeated freeze-thaw cycles (up to 6 cycles), and oral sampling location on DNA extraction and on genetic analysis from saliva were negligible.</p> <p>Conclusions</p> <p>Whole saliva samples with volumes of at least .10 ml were sufficient to extract good quality and quantity DNA. Using 10 ng of DNA per genotyping reaction, the obtained samples can be used for more than one hundred candidate gene assays. When saliva is collected with an absorbent device, most of the nucleic acid content remains in the device, therefore it is advisable to collect the device separately for later genetic analyses.</p

HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis

A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease

Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association studies (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of 185 thousand CAD cases and controls, interrogating 6.7 million common (MAF>0.05) as well as 2.7 million low frequency (0.005<MAF<0.05) variants. In addition to confirmation of most known CAD loci, we identified 10 novel loci, eight additive and two recessive, that contain candidate genes that newly implicate biological processes in vessel walls. We observed intra-locus allelic heterogeneity but little evidence of low frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect siz

The danger of mapping risk from multiple natural hazards

In recent decades, society has been greatly affected by natural disasters (e.g. floods, droughts, earthquakes), losses and effects caused by these disasters have been increasing. Conventionally, risk assessment focuses on individual hazards, but the importance of addressing multiple hazards is now recognised. Two approaches exist to assess risk from multiple-hazards; the risk index (addressing hazards, and the exposure and vulnerability of people or property at risk) and the mathematical statistics method (which integrates observations of past losses attributed to each hazard type). These approaches have not previously been compared. Our application of both to China clearly illustrates their inconsistency. For example, from 31 Chinese provinces assessed for multi-hazard risk, Gansu and Sichuan provinces are at low risk of life loss with the risk index approach, but high risk using the mathematical statistics approach. Similarly, Tibet is identified as being at almost the highest risk of economic loss using the risk index, but lowest risk under the mathematical statistics approach. Such inconsistency should be recognised if risk is to be managed effectively, whilst the practice of multi-hazard risk assessment needs to incorporate the relative advantages of both approaches