The what and where of adding channel noise to the Hodgkin-Huxley equations

One of the most celebrated successes in computational biology is the Hodgkin-Huxley framework for modeling electrically active cells. This framework, expressed through a set of differential equations, synthesizes the impact of ionic currents on a cell's voltage -- and the highly nonlinear impact of that voltage back on the currents themselves -- into the rapid push and pull of the action potential. Latter studies confirmed that these cellular dynamics are orchestrated by individual ion channels, whose conformational changes regulate the conductance of each ionic current. Thus, kinetic equations familiar from physical chemistry are the natural setting for describing conductances; for small-to-moderate numbers of channels, these will predict fluctuations in conductances and stochasticity in the resulting action potentials. At first glance, the kinetic equations provide a far more complex (and higher-dimensional) description than the original Hodgkin-Huxley equations. This has prompted more than a decade of efforts to capture channel fluctuations with noise terms added to the Hodgkin-Huxley equations. Many of these approaches, while intuitively appealing, produce quantitative errors when compared to kinetic equations; others, as only very recently demonstrated, are both accurate and relatively simple. We review what works, what doesn't, and why, seeking to build a bridge to well-established results for the deterministic Hodgkin-Huxley equations. As such, we hope that this review will speed emerging studies of how channel noise modulates electrophysiological dynamics and function. We supply user-friendly Matlab simulation code of these stochastic versions of the Hodgkin-Huxley equations on the ModelDB website (accession number 138950) and http://www.amath.washington.edu/~etsb/tutorials.html.Comment: 14 pages, 3 figures, review articl

The Formation and Evolution of the First Massive Black Holes

The first massive astrophysical black holes likely formed at high redshifts (z>10) at the centers of low mass (~10^6 Msun) dark matter concentrations. These black holes grow by mergers and gas accretion, evolve into the population of bright quasars observed at lower redshifts, and eventually leave the supermassive black hole remnants that are ubiquitous at the centers of galaxies in the nearby universe. The astrophysical processes responsible for the formation of the earliest seed black holes are poorly understood. The purpose of this review is threefold: (1) to describe theoretical expectations for the formation and growth of the earliest black holes within the general paradigm of hierarchical cold dark matter cosmologies, (2) to summarize several relevant recent observations that have implications for the formation of the earliest black holes, and (3) to look into the future and assess the power of forthcoming observations to probe the physics of the first active galactic nuclei.Comment: 39 pages, review for "Supermassive Black Holes in the Distant Universe", Ed. A. J. Barger, Kluwer Academic Publisher

Phenomenological Implications of Deflected Mirage Mediation: Comparison with Mirage Mediation

We compare the collider phenomenology of mirage mediation and deflected mirage mediation, which are two recently proposed "mixed" supersymmetry breaking scenarios motivated from string compactifications. The scenarios differ in that deflected mirage mediation includes contributions from gauge mediation in addition to the contributions from gravity mediation and anomaly mediation also present in mirage mediation. The threshold effects from gauge mediation can drastically alter the low energy spectrum from that of pure mirage mediation models, resulting in some cases in a squeezed gaugino spectrum and a gluino that is much lighter than other colored superpartners. We provide several benchmark deflected mirage mediation models and construct model lines as a function of the gauge mediation contributions, and discuss their discovery potential at the LHC.Comment: 29 pages, 9 figure

Cellular Radiosensitivity: How much better do we understand it?

Purpose: Ionizing radiation exposure gives rise to a variety of lesions in DNA that result in genetic instability and potentially tumorigenesis or cell death. Radiation extends its effects on DNA by direct interaction or by radiolysis of H2O that generates free radicals or aqueous electrons capable of interacting with and causing indirect damage to DNA. While the various lesions arising in DNA after radiation exposure can contribute to the mutagenising effects of this agent, the potentially most damaging lesion is the DNA double strand break (DSB) that contributes to genome instability and/or cell death. Thus in many cases failure to recognise and/or repair this lesion determines the radiosensitivity status of the cell. DNA repair mechanisms including homologous recombination (HR) and non-homologous end-joining (NHEJ) have evolved to protect cells against DNA DSB. Mutations in proteins that constitute these repair pathways are characterised by radiosensitivity and genome instability. Defects in a number of these proteins also give rise to genetic disorders that feature not only genetic instability but also immunodeficiency, cancer predisposition, neurodegeneration and other pathologies. Conclusions: In the past fifty years our understanding of the cellular response to radiation damage has advanced enormously with insight being gained from a wide range of approaches extending from more basic early studies to the sophisticated approaches used today. In this review we discuss our current understanding of the impact of radiation on the cell and the organism gained from the array of past and present studies and attempt to provide an explanation for what it is that determines the response to radiation

Identification of Trypanosome Proteins in Plasma from African Sleeping Sickness Patients Infected with T. b. rhodesiense

Control of human African sleeping sickness, caused by subspecies of the protozoan parasite Trypanosoma brucei, is based on preventing transmission by elimination of the tsetse vector and by active diagnostic screening and treatment of infected patients. To identify trypanosome proteins that have potential as biomarkers for detection and monitoring of African sleeping sickness, we have used a ‘deep-mining” proteomics approach to identify trypanosome proteins in human plasma. Abundant human plasma proteins were removed by immunodepletion. Depleted plasma samples were then digested to peptides with trypsin, fractionated by basic reversed phase and each fraction analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This sample processing and analysis method enabled identification of low levels of trypanosome proteins in pooled plasma from late stage sleeping sickness patients infected with Trypanosoma brucei rhodesiense. A total of 254 trypanosome proteins were confidently identified. Many of the parasite proteins identified were of unknown function, although metabolic enzymes, chaperones, proteases and ubiquitin-related/acting proteins were found. This approach to the identification of conserved, soluble trypanosome proteins in human plasma offers a possible route to improved disease diagnosis and monitoring, since these molecules are potential biomarkers for the development of a new generation of antigen-detection assays. The combined immuno-depletion/mass spectrometric approach can be applied to a variety of infectious diseases for unbiased biomarker identification

Mislocalisation of BEST1 in iPSC-derived retinal pigment epithelial cells from a family with autosomal dominant vitreoretinochoroidopathy (ADVIRC)

Autosomal dominant vitreoretinochoroidopathy (ADVIRC) is a rare, early-onset retinal dystrophy characterised by distinct bands of circumferential pigmentary degeneration in the peripheral retina and developmental eye defects. ADVIRC is caused by mutations in the Bestrophin1 (BEST1) gene, which encodes a transmembrane protein thought to function as an ion channel in the basolateral membrane of retinal pigment epithelial (RPE) cells. Previous studies suggest that the distinct ADVIRC phenotype results from alternative splicing of BEST1 pre-mRNA. Here, we have used induced pluripotent stem cell (iPSC) technology to investigate the effects of an ADVIRC associated BEST1 mutation (c.704T > C, p.V235A) in patient-derived iPSC-RPE. We found no evidence of alternate splicing of the BEST1 transcript in ADVIRC iPSC-RPE, however in patient-derived iPSC-RPE, BEST1 was expressed at the basolateral membrane and the apical membrane. During human eye development we show that BEST1 is expressed more abundantly in peripheral RPE compared to central RPE and is also expressed in cells of the developing retina. These results suggest that higher levels of mislocalised BEST1 expression in the periphery, from an early developmental stage, could provide a mechanism that leads to the distinct clinical phenotype observed in ADVIRC patients

Does sex matter in the associations between classic risk factors and fatal coronary heart disease in populations from the Asia-Pacific region?

Background: There is much interest in promoting healthy heart awareness among women. However, little is known about the reasons behind the lower rates of heart disease among women compared with men, and why this risk difference diminishes with age. Previous comparative studies have generally had insufficient numbers of women to quantify such differences reliably. Methods: We carried out an individual participant data meta-analysis of 39 cohort studies (32 from Asian countries and 7 from Australia and New Zealand). Cox models were used to estimate hazard ratios (HR) for coronary death, comparing men to women. Further adjustments were made for several proven coronary risk factors to quantify their contributions to the sex differential. Sex interactions were tested for the same risk factors. Results: During 4 million person-years of follow-up, there were 1989 (926 female) deaths from coronary heart disease (CHD). The age-adjusted and study-adjusted male/female HR (95% confidence interval [95% CI]) was 2.05 (1.89-2.22). At baseline, 54% of men vs. 7% of women were current smokers; hence, adjustment for smoking explained the largest component (20%) of this HR. A significant sex interaction was observed between systolic blood pressure (SBP) and CHD mortality such that a 10 mm Hg increase was associated with a 15% greater increase in the relative risk (RR) of coronary death in women compared with men (p = 0.002). Conclusions: Only a small amount of the sex differential in coronary death could be explained by differences in the prevalence of classic risk factors. Alternative explanations are required to explain the age-related attenuation of the sex difference in CHD risk. © Mary Ann Liebert, Inc.published_or_final_versio

Removal of various contaminants from water by renewable lignocellulose-derived biosorbents: a comprehensive and critical review

© 2019, © 2019 Taylor & Francis Group, LLC. Contaminants in water bodies cause potential health risks for humans and great environmental threats. Therefore, the development and exploration of low-cost, promising adsorbents to remove contaminants from water resources as a sustainable option is one focus of the scientific community. Here, we conducted a critical review regarding the application of pristine and modified/treated biosorbents derived from leaves for the removal of various contaminants. These include potentially toxic cationic and oxyanionic metal ions, radioactive metal ions, rare earth elements, organic cationic and anionic dyes, phosphate, ammonium, and fluoride from water media. Similar to lignocellulose-based biosorbents, leaf-based biosorbents exhibit a low specific surface area and total pore volume but have abundant surface functional groups, high concentrations of light metals, and a high net surface charge density. The maximum adsorption capacity of biosorbents strongly depends on the operation conditions, experiment types, and adsorbate nature. The absorption mechanism of contaminants onto biosorbents is complex; therefore, typical experiments used to identify the primary mechanism of the adsorption of contaminants onto biosorbents were thoroughly discussed. It was concluded that byproduct leaves are renewable, biodegradable, and promising biosorbents which have the potential to be used as a low-cost green alternative to commercial activated carbon for effective removal of various contaminants from the water environment in the real-scale plants

Using the RDP Classifier to Predict Taxonomic Novelty and Reduce the Search Space for Finding Novel Organisms

BACKGROUND: Currently, the naïve Bayesian classifier provided by the Ribosomal Database Project (RDP) is one of the most widely used tools to classify 16S rRNA sequences, mainly collected from environmental samples. We show that RDP has 97+% assignment accuracy and is fast for 250 bp and longer reads when the read originates from a taxon known to the database. Because most environmental samples will contain organisms from taxa whose 16S rRNA genes have not been previously sequenced, we aim to benchmark how well the RDP classifier and other competing methods can discriminate these novel taxa from known taxa. PRINCIPAL FINDINGS: Because each fragment is assigned a score (containing likelihood or confidence information such as the boostrap score in the RDP classifier), we "train" a threshold to discriminate between novel and known organisms and observe its performance on a test set. The threshold that we determine tends to be conservative (low sensitivity but high specificity) for naïve Bayesian methods. Nonetheless, our method performs better with the RDP classifier than the other methods tested, measured by the f-measure and the area-under-the-curve on the receiver operating characteristic of the test set. By constraining the database to well-represented genera, sensitivity improves 3-15%. Finally, we show that the detector is a good predictor to determine novel abundant taxa (especially for finer levels of taxonomy where novelty is more likely to be present). CONCLUSIONS: We conclude that selecting a read-length appropriate RDP bootstrap score can significantly reduce the search space for identifying novel genera and higher levels in taxonomy. In addition, having a well-represented database significantly improves performance while having genera that are "highly" similar does not make a significant improvement. On a real dataset from an Amazon Terra Preta soil sample, we show that the detector can predict (or correlates to) whether novel sequences will be assigned to new taxa when the RDP database "doubles" in the future