Chemical and Hydrodynamic Mechanisms for Long-Term Geological Carbon Storage

Geological storage of CO₂ (GCS), also referred to as carbon sequestration, is a critical component for decreasing anthropogenic CO₂ atmospheric emissions. Stored CO₂ will exist as a supercritical phase, most likely in deep, saline, sedimentary reservoirs. Research at the Center for Frontiers of Subsurface Energy Security (CFSES), a Department of Energy, Energy Frontier Research Center, provides insights into the storage process. The integration of pore-scale experiments, molecular dynamics simulations, and study of natural analogue sites has enabled understanding of the efficacy of capillary, solubility, and dissolution trapping of CO₂ for GCS. Molecular dynamics simulations provide insight on relative wetting of supercritical CO₂ and brine hydrophilic and hydrophobic basal surfaces of kaolinite. Column experiments of successive supercritical CO₂/brine flooding with high-resolution X-ray computed tomography imaging show a greater than 10% difference of residual trapping of CO₂ in hydrophobic media compared to hydrophilic media that trapped only 2% of the CO₂. Simulation results suggest that injecting a slug of nanoparticle dispersion into the storage reservoir before starting CO₂ injection could increase the overall efficiency of large-scale storage. We estimate that approximately 22% ± 17% of the initial CO₂ emplaced into the Bravo Dome field site of New Mexico has dissolved into the underlying brine. The rate of CO₂ dissolution may be considered limited over geological timescales. Field observations at the Little Grand Wash fault in Utah suggest that calcite precipitation results in shifts in preferential flow paths of the upward migrating CO₂-saturated-brine. Results of hybrid pore-scale and pore network modeling based on Little Grand Wash fault observations demonstrate that inclusion of realistic pore configurations, flow and transport physics, and geochemistry are needed to enhance our fundamental mechanistic explanations of how calcite precipitation alters flow paths by pore plugging to match the Little Grand Wash fault observations

Brief Overview of Bioinformatics Activities in Singapore

10.1371/journal.pcbi.1000508PLoS Computational Biology5

Reporting randomised clinical trials of analgesics after traumatic or orthopaedic surgery is inadequate: a systematic review

Background Several randomised clinical trials (RCTs) of analgesics in postoperative pain after traumatic or orthopaedic surgery (TOS) have been published, but no studies have assessed the quality of these reports. We aimed to examine the quality of reporting RCTs on analgesics for postoperative pain after TOS. Methods Reports of RCTs assessing analgesics in postoperative pain after TOS were systematically searched from electronic databases. The quality of reports was assessed using the CONSORT checklist (scoring range from 0 to 22). The quality was considered poor when scoring was 12 or lesser. The publication year and the impact factor of journals were recorded. Results A total of 92 reports of RCTs were identified and 69 (75%) scored 12 or lesser in CONSORT checklist (range 5-17). The mean (SD) CONSORT score of all reports was 10.6 (2.7). Missing CONSORT items included primary and secondary outcome measures (11%), the specific objectives and hypothesis definition (12%), the sample size calculation (12%), the dates defining the periods of recruitment (12%), the discussion of external validity of findings (14%), the allocation sequence generation (24%), and the interpretation of potential bias or imprecision of results (25%). There was a little improvement in CONSORT scores over time (r = 0.62; p < 0.001) and with impact factor of journals (r = 0.30; p < 0.001). Conclusion Quality of reporting RCTs on analgesics after TOS is poor. Reporting of those RCTs should be improved according to methodological standard checklists in the next years

Development and validation of Prediction models for Risks of complications in Early-onset Pre-eclampsia (PREP):a prospective cohort study

Background: The prognosis of early-onset pre-eclampsia (before 34 weeks’ gestation) is variable. Accurate prediction of complications is required to plan appropriate management in high-risk women. Objective: To develop and validate prediction models for outcomes in early-onset pre-eclampsia. Design: Prospective cohort for model development, with validation in two external data sets. Setting: Model development: 53 obstetric units in the UK. Model transportability: PIERS (Pre-eclampsia Integrated Estimate of RiSk for mothers) and PETRA (Pre-Eclampsia TRial Amsterdam) studies. Participants: Pregnant women with early-onset pre-eclampsia. Sample size: Nine hundred and forty-six women in the model development data set and 850 women (634 in PIERS, 216 in PETRA) in the transportability (external validation) data sets. Predictors: The predictors were identified from systematic reviews of tests to predict complications in pre-eclampsia and were prioritised by Delphi survey. Main outcome measures: The primary outcome was the composite of adverse maternal outcomes established using Delphi surveys. The secondary outcome was the composite of fetal and neonatal complications. Analysis: We developed two prediction models: a logistic regression model (PREP-L) to assess the overall risk of any maternal outcome until postnatal discharge and a survival analysis model (PREP-S) to obtain individual risk estimates at daily intervals from diagnosis until 34 weeks. Shrinkage was used to adjust for overoptimism of predictor effects. For internal validation (of the full models in the development data) and external validation (of the reduced models in the transportability data), we computed the ability of the models to discriminate between those with and without poor outcomes (c-statistic), and the agreement between predicted and observed risk (calibration slope). Results: The PREP-L model included maternal age, gestational age at diagnosis, medical history, systolic blood pressure, urine protein-to-creatinine ratio, platelet count, serum urea concentration, oxygen saturation, baseline treatment with antihypertensive drugs and administration of magnesium sulphate. The PREP-S model additionally included exaggerated tendon reflexes and serum alanine aminotransaminase and creatinine concentration. Both models showed good discrimination for maternal complications, with an optimism-adjusted c-statistic of 0.82 [95% confidence interval (CI) 0.80 to 0.84] for PREP-L and 0.75 (95% CI 0.73 to 0.78) for the PREP-S model in the internal validation. External validation of the reduced PREP-L model showed good performance with a c-statistic of 0.81 (95% CI 0.77 to 0.85) in PIERS and 0.75 (95% CI 0.64 to 0.86) in PETRA cohorts for maternal complications, and calibrated well with slopes of 0.93 (95% CI 0.72 to 1.10) and 0.90 (95% CI 0.48 to 1.32), respectively. In the PIERS data set, the reduced PREP-S model had a c-statistic of 0.71 (95% CI 0.67 to 0.75) and a calibration slope of 0.67 (95% CI 0.56 to 0.79). Low gestational age at diagnosis, high urine protein-to-creatinine ratio, increased serum urea concentration, treatment with antihypertensive drugs, magnesium sulphate, abnormal uterine artery Doppler scan findings and estimated fetal weight below the 10th centile were associated with fetal complications. Conclusions: The PREP-L model provided individualised risk estimates in early-onset pre-eclampsia to plan management of high-or low-risk individuals. The PREP-S model has the potential to be used as a triage tool for risk assessment. The impacts of the model use on outcomes need further evaluation

Impact of hormonal treatment duration in combination with radiotherapy for locally advanced prostate cancer: Meta-analysis of randomized trials

<p>Abstract</p> <p>Background</p> <p>Hormone therapy plus radiotherapy significantly decreases recurrences and mortality of patients affected by locally advanced prostate cancer. In order to determine if difference exists according to the hormonal treatment duration, a literature-based meta-analysis was performed.</p> <p>Methods</p> <p>Relative risks (RR) were derived through a random-effect model. Differences in primary (biochemical failure, BF; cancer-specific survival, CSS), and secondary outcomes (overall survival, OS; local or distant recurrence, LR/DM) were explored. Absolute differences (AD) and the number needed to treat (NNT) were calculated. Heterogeneity, a meta-regression for clinic-pathological predictors and a correlation test for surrogates were conducted.</p> <p>Results</p> <p>Five trials (3,424 patients) were included. Patient population ranged from 267 to 1,521 patients. The longer hormonal treatment significantly improves BF (with significant heterogeneity) with an absolute benefit of 10.1%, and a non significant trend in CSS. With regard to secondary end-points, the longer hormonal treatment significantly decrease both the LR and the DM with an absolute difference of 11.7% and 11.5%. Any significant difference in OS was observed. None of the three identified clinico-pathological predictors (median PSA, range 9.5-20.35, Gleason score 7-10, 27-55% patients/trial, and T3-4, 13-77% patients/trial), did significantly affect outcomes. At the meta-regression analysis a significant correlation between the overall treatment benefit in BF, CSS, OS, LR and DM, and the length of the treatment was found (p≤0.03).</p> <p>Conclusions</p> <p>Although with significant heterogeneity (reflecting different patient' risk stratifications), a longer hormonal treatment duration significantly decreases biochemical, local and distant recurrences, with a trend for longer cancer specific survival.</p

Rise and Demise of Bioinformatics? Promise and Progress

The field of bioinformatics and computational biology has gone through a number of transformations during the past 15 years, establishing itself as a key component of new biology. This spectacular growth has been challenged by a number of disruptive changes in science and technology. Despite the apparent fatigue of the linguistic use of the term itself, bioinformatics has grown perhaps to a point beyond recognition. We explore both historical aspects and future trends and argue that as the field expands, key questions remain unanswered and acquire new meaning while at the same time the range of applications is widening to cover an ever increasing number of biological disciplines. These trends appear to be pointing to a redefinition of certain objectives, milestones, and possibly the field itself

Network Modeling Identifies Molecular Functions Targeted by miR-204 to Suppress Head and Neck Tumor Metastasis

Due to the large number of putative microRNA gene targets predicted by sequence-alignment databases and the relative low accuracy of such predictions which are conducted independently of biological context by design, systematic experimental identification and validation of every functional microRNA target is currently challenging. Consequently, biological studies have yet to identify, on a genome scale, key regulatory networks perturbed by altered microRNA functions in the context of cancer. In this report, we demonstrate for the first time how phenotypic knowledge of inheritable cancer traits and of risk factor loci can be utilized jointly with gene expression analysis to efficiently prioritize deregulated microRNAs for biological characterization. Using this approach we characterize miR-204 as a tumor suppressor microRNA and uncover previously unknown connections between microRNA regulation, network topology, and expression dynamics. Specifically, we validate 18 gene targets of miR-204 that show elevated mRNA expression and are enriched in biological processes associated with tumor progression in squamous cell carcinoma of the head and neck (HNSCC). We further demonstrate the enrichment of bottleneckness, a key molecular network topology, among miR-204 gene targets. Restoration of miR-204 function in HNSCC cell lines inhibits the expression of its functionally related gene targets, leads to the reduced adhesion, migration and invasion in vitro and attenuates experimental lung metastasis in vivo. As importantly, our investigation also provides experimental evidence linking the function of microRNAs that are located in the cancer-associated genomic regions (CAGRs) to the observed predisposition to human cancers. Specifically, we show miR-204 may serve as a tumor suppressor gene at the 9q21.1–22.3 CAGR locus, a well established risk factor locus in head and neck cancers for which tumor suppressor genes have not been identified. This new strategy that integrates expression profiling, genetics and novel computational biology approaches provides for improved efficiency in characterization and modeling of microRNA functions in cancer as compared to the state of art and is applicable to the investigation of microRNA functions in other biological processes and diseases

Development and evaluation of an instrument for the critical appraisal of randomized controlled trials of natural products

<p>Abstract</p> <p>Background</p> <p>The efficacy of natural products (NPs) is being evaluated using randomized controlled trials (RCTs) with increasing frequency, yet a search of the literature did not identify a widely accepted critical appraisal instrument developed specifically for use with NPs. The purpose of this project was to develop and evaluate a critical appraisal instrument that is sufficiently rigorous to be used in evaluating RCTs of conventional medicines, and also has a section specific for use with single entity NPs, including herbs and natural sourced chemicals.</p> <p>Methods</p> <p>Three phases of the project included: 1) using experts and a Delphi process to reach consensus on a list of items essential in describing the identity of an NP; 2) compiling a list of non-NP items important for evaluating the quality of an RCT using systematic review methodology to identify published instruments and then compiling item categories that were part of a validated instrument and/or had empirical evidence to support their inclusion and 3) conducting a field test to compare the new instrument to a published instrument for usefulness in evaluating the quality of 3 RCTs of a NP and in applying results to practice.</p> <p>Results</p> <p>Two Delphi rounds resulted in a list of 15 items essential in describing NPs. Seventeen item categories fitting inclusion criteria were identified from published instruments for conventional medicines. The new assessment instrument was assembled based on content of the two lists and the addition of a Reviewer's Conclusion section. The field test of the new instrument showed good criterion validity. Participants found it useful in translating evidence from RCTs to practice.</p> <p>Conclusion</p> <p>A new instrument for the critical appraisal of RCTs of NPs was developed and tested. The instrument is distinct from other available assessment instruments for RCTs of NPs in its systematic development and validation. The instrument is ready to be used by pharmacy students, health care practitioners and academics and will continue to be refined as required.</p