Spectral statistics of the quenched normal modes of a network-forming molecular liquid

We evaluate the density of states of the quenched normal modes of ST2 water, and their statistical fluctuations, for a range of densities spanning three regimes of behavior of a hydrogen bonded liquid: a lower-density regime of random tetrahedral network formation; in the vicinity of a liquid-liquid critical point; and in a higher-density regime of fragile glass-forming behavior. For all cases we find that the fluctuations around the mean spectral densities obey the predictions of the Gaussian orthogonal ensemble of random matrix theory. We also measure the participation ratio of the normal modes across the entire frequency range, and find behavior consistent with the majority of modes being of an extended nature, rather than localized.Comment: Accepted for publication in The Journal of Chemical Physic

Sparse random matrices and vibrational spectra of amorphous solids

A random matrix approach is used to analyze the vibrational properties of amorphous solids. We investigated a dynamical matrix M=AA^T with non-negative eigenvalues. The matrix A is an arbitrary real NxN sparse random matrix with n independent non-zero elements in each row. The average values =0 and dispersion =V^2 for all non-zero elements. The density of vibrational states g(w) of the matrix M for N,n >> 1 is given by the Wigner quarter circle law with radius independent of N. We argue that for n^2 << N this model can be used to describe the interaction of atoms in amorphous solids. The level statistics of matrix M is well described by the Wigner surmise and corresponds to repulsion of eigenfrequencies. The participation ratio for the major part of vibrational modes in three dimensional system is about 0.2 - 0.3 and independent of N. Together with term repulsion it indicates clearly to the delocalization of vibrational excitations. We show that these vibrations spread in space by means of diffusion. In this respect they are similar to diffusons introduced by Allen, Feldman, et al., Phil. Mag. B 79, 1715 (1999) in amorphous silicon. Our results are in a qualitative and sometimes in a quantitative agreement with molecular dynamic simulations of real and model glasses.Comment: 24 pages, 7 figure

Artificial Neural Network Inference (ANNI): A Study on Gene-Gene Interaction for Biomarkers in Childhood Sarcomas

Objective: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI). Method: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs) dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. Results: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS); FCGRT and OLFM1 in Ewing’s sarcoma (EWS)) suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. Conclusions: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas

Creation of an institutional preoperative checklist to support clinical risk assessment in patients with ulcerative colitis (UC) considering ileoanal pouch surgery

Background: Total proctocolectomy with ileal pouch–anal anastomosis (IPAA) is the most established restorative operative approach for patients with ulcerative colitis. It has associated morbidity and the potential for major repercussions on quality of life. As such, patient selection is crucial to its success. The main aim of this paper is to present an institutional preoperative checklist to support clinical risk assessment and patient selection in those considering IPAA. Methods: A literature review was performed to identify the risk factors associated with surgical complications, decreased functional outcomes/quality of life, and pouch failure after IPAA. Based on this, a preliminary checklist was devised and modified through an iterative process. This was then evaluated by a consensus group comprising the pouch multidisciplinary team (MDT) core members. Results: The final preoperative checklist includes assessment for risk factors such as gender, advanced age, obesity, comorbidities, sphincteric impairment, Crohn’s disease and pelvic radiation therapy. In addition, essential steps in the decision-making process, such as pouch nurse counselling and discussion regarding surgical alternatives, are also included. The last step of the checklist is discussion at a dedicated pouch-MDT. Discussion: A preoperative checklist may support clinicians with the selection of patients that are suitable for pouch surgery. It also serves as a useful tool to inform the discussion of cases at the MDT meeting

A simpler method of preprocessing MALDI-TOF MS data for differential biomarker analysis: stem cell and melanoma cancer studies

<p>Abstract</p> <p>Introduction</p> <p>Raw spectral data from matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) with MS profiling techniques usually contains complex information not readily providing biological insight into disease. The association of identified features within raw data to a known peptide is extremely difficult. Data preprocessing to remove uncertainty characteristics in the data is normally required before performing any further analysis. This study proposes an alternative yet simple solution to preprocess raw MALDI-TOF-MS data for identification of candidate marker ions. Two in-house MALDI-TOF-MS data sets from two different sample sources (melanoma serum and cord blood plasma) are used in our study.</p> <p>Method</p> <p>Raw MS spectral profiles were preprocessed using the proposed approach to identify peak regions in the spectra. The preprocessed data was then analysed using bespoke machine learning algorithms for data reduction and ion selection. Using the selected ions, an ANN-based predictive model was constructed to examine the predictive power of these ions for classification.</p> <p>Results</p> <p>Our model identified 10 candidate marker ions for both data sets. These ion panels achieved over 90% classification accuracy on blind validation data. Receiver operating characteristics analysis was performed and the area under the curve for melanoma and cord blood classifiers was 0.991 and 0.986, respectively.</p> <p>Conclusion</p> <p>The results suggest that our data preprocessing technique removes unwanted characteristics of the raw data, while preserving the predictive components of the data. Ion identification analysis can be carried out using MALDI-TOF-MS data with the proposed data preprocessing technique coupled with bespoke algorithms for data reduction and ion selection.</p

Impacts of the Last Glacial Cycle on ground surface temperature reconstructions over the last millennium

Borehole temperature profiles provide robust estimates of past ground surface temperature changes, in agreement with meteorological data. Nevertheless, past climatic changes such as the Last Glacial Cycle (LGC) generated thermal effects in the subsurface that affect estimates of recent climatic change from geothermal data. We use an ensemble of ice sheet simulations spanning the last 120 ka to assess the impact of the Laurentide Ice Sheet on recent ground surface temperature histories reconstructed from borehole temperature profiles over North America. When the thermal remnants of the LGC are removed, we find larger amounts of subsurface heat storage (2.8 times) and an increased warming of the ground surface over North America by 0.75 K, both relative to uncorrected borehole estimates

Role of Haptoglobin in Polycystic Ovary Syndrome (PCOS), Obesity and Disorders of Glucose Tolerance in Premenopausal Women

alleles of the haptoglobin α–chain polymorphism reduce the anti-oxidant properties and increase the pro-inflammatory actions of this acute-phase protein in a gene-dosage fashion. We hypothesized that the haptoglobin polymorphism might contribute to the increased oxidative stress and low-grade chronic inflammation frequently associated with polycystic ovary syndrome, obesity, and abnormalities of glucose tolerance.<0.001), yet no association was found between obesity and haptoglobin genotypes. No differences were observed in haptoglobin levels or genotype frequencies depending on glucose tolerance. Fifty percent of the variation in serum haptoglobin concentrations was explained by the variability in serum C-reactive protein concentrations, BMI, insulin sensitivity and haptoglobin genotypes. alleles suggests that the anti-oxidant and anti-inflammatory properties of haptoglobin may be reduced in these patients

Lipidomic analysis of plasma samples from women with polycystic ovary syndrome

Abstract Polycystic ovary syndrome (PCOS) is a common disorder affecting between 5 and 18 % of females of reproductive age and can be diagnosed based on a combination of clinical, ultrasound and biochemical features, none of which on its own is diagnostic. A lipidomic approach using liquid chromatography coupled with accurate mass high-resolution mass-spectrometry (LCHRMS) was used to investigate if there were any differences in plasma lipidomic profiles in women with PCOS compared with control women at different stages of menstrual cycle. Plasma samples from 40 women with PCOS and 40 controls aged between 18 and 40 years were analysed in combination with multivariate statistical analyses. Multivariate data analysis (LASSO regression and OPLSDA) of the sample lipidomics datasets showed a weak prediction model for PCOS versus control samples from the follicular and mid-cycle phases of the menstrual cycle, but a stronger model (specificity 85 % and sensitivity 95 %) for PCOS versus the luteal phase menstrual cycle controls. The PCOS vs luteal phase model showed increased levels of plasma triglycerides and sphingomyelins and decreased levels of lysophosphatidylcholines and phosphatidylethanolamines in PCOS women compared with controls. Lipid biomarkers of PCOS were tentatively identified which may be useful in distinguishing PCOS from controls especially when performed during the menstrual cycle luteal phase

A Computational Model of the Ionic Currents, Ca2+ Dynamics and Action Potentials Underlying Contraction of Isolated Uterine Smooth Muscle

Uterine contractions during labor are discretely regulated by rhythmic action potentials (AP) of varying duration and form that serve to determine calcium-dependent force production. We have employed a computational biology approach to develop a fuller understanding of the complexity of excitation-contraction (E-C) coupling of uterine smooth muscle cells (USMC). Our overall aim is to establish a mathematical platform of sufficient biophysical detail to quantitatively describe known uterine E-C coupling parameters and thereby inform future empirical investigations of physiological and pathophysiological mechanisms governing normal and dysfunctional labors. From published and unpublished data we construct mathematical models for fourteen ionic currents of USMCs: currents (L- and T-type), current, an hyperpolarization-activated current, three voltage-gated currents, two -activated current, -activated current, non-specific cation current, - exchanger, - pump and background current. The magnitudes and kinetics of each current system in a spindle shaped single cell with a specified surface area∶volume ratio is described by differential equations, in terms of maximal conductances, electrochemical gradient, voltage-dependent activation/inactivation gating variables and temporal changes in intracellular computed from known fluxes. These quantifications are validated by the reconstruction of the individual experimental ionic currents obtained under voltage-clamp. Phasic contraction is modeled in relation to the time constant of changing . This integrated model is validated by its reconstruction of the different USMC AP configurations (spikes, plateau and bursts of spikes), the change from bursting to plateau type AP produced by estradiol and of simultaneous experimental recordings of spontaneous AP, and phasic force. In summary, our advanced mathematical model provides a powerful tool to investigate the physiological ionic mechanisms underlying the genesis of uterine electrical E-C coupling of labor and parturition. This will furnish the evolution of descriptive and predictive quantitative models of myometrial electrogenesis at the whole cell and tissue levels

A prospective study of patient safety incidents in gastrointestinal endoscopy

Background and study aims Medical error occurs frequently with significant morbidity and mortality. This study aime to assess the frequency and type of endoscopy patient safety incidents (PSIs). Patients and methods A prospective observational study of PSIs in routine diagnostic and therapeutic endoscopy was undertaken in a secondary and tertiary care center. Observations were undertaken within the endoscopy suite across pre-procedure, intra-procedure and post-procedure phases of care. Experienced (Consultant-level) and trainee endoscopists from medical, surgical, and nursing specialities were included. PSIs were defined as any safety issue that had the potential to or directly adversely affected patient care: PSIs included near misses, complications, adverse events and "never events". PSIs were reviewed by an expert panel and categorized for severity and nature via expert consensus. Results One hundred and forty procedures (92 diagnostic, 48 therapeutic) over 37 lists (experienced operators n = 25, trainees n = 12) were analyzed. One hundred forty PSIs were identified (median 1 per procedure, range 0 - 7). Eighty-six PSIs (61 %) occurred in 48 therapeutic procedures. Zero PSIs were detected in 13 diagnostic procedures. 21 (15 %) PSIs were categorized as severe and 12 (9 %) had the potential to be "never events," including patient misidentification and wrong procedure. Forty PSIs (28 %) were of intermediate severity and 78 (56 %) were minor. Oxygen monitoring PSIs occurred most frequently. Conclusion This is the first study documenting the range and frequency of PSIs in endoscopy. Although many errors are minor without immediate consequence, further work should identify whether prevention of such recurrent errors affects the incidence of severe errors, thus improving safety and quality