Analysis of gas chromatography/mass spectrometry data for catalytic lignin depolymerization using positive matrix factorization

Various catalytic technologies are being developed to efficiently convert lignin into renewable chemicals. However, due to its complexity, catalytic lignin depolymerization often generates a wide and complex distribution of product compounds. Gas chromatography/mass spectrometry (GC-MS) is a common analytical technique to profile the compounds that comprise lignin depolymerization products. GC-MS is applied not only to determine the product composition, but also to develop an understanding of the catalytic reaction pathways and of the relationships among catalyst structure, reaction conditions, and the resulting compounds generated. Although a very useful tool, the analysis of lignin depolymerization products with GC-MS is limited by the quality and scope of the available mass spectral libraries and the ability to correlate changes in GC-MS chromatograms to changes in lignin structure, catalyst structure, and other reaction conditions. In this study, the GC-MS data of the depolymerization products generated from organosolv hybrid poplar lignin using a copper-doped porous metal oxide catalyst and a methanol/dimethyl carbonate co-solvent was analyzed by applying a factor analysis technique, positive matrix factorization (PMF). Several different solutions for the PMF model were explored. A 13-factor solution sufficiently explains the chemical changes occurring to lignin depolymerization products as a function of lignin, reaction time, catalyst, and solvent. Overall, seven factors were found to represent aromatic compounds, while one factor was defined by aliphatic compounds

Methods of classification for women undergoing induction of labour: a systematic review and novel classification system

OBJECTIVE To develop and demonstrate the applicability of a classification system for induction of labour (IOL) that fulfils recognised classification system attributes for clinical, surveillance and research purposes. DESIGN Proof of concept. SETTING, POPULATION Applicability demonstrated in a population cohort of 909,702 maternities in New South Wales, Australia, 2002-2011. METHODS A multidisciplinary collaboration developed a classification system through a systematic literature review, development of a clinically logical model, and presentation to stakeholders for feedback and refinement. Classification factors included parity (nulliparous, parous), previous caesarean section (CS), gestational age (≤36, 37-38, 39-40, ≥41 weeks gestation), number (singleton, multiple) and presentation of the fetus (cephalic, non-cephalic). We determined: the size of each classification group, the contribution each group made to overall IOL rates, and within-group IOL rates (calculated as proportions of all maternities, all maternities excluding prelabour CS and of all continuing maternities). MAIN OUTCOME MEASURES Applicability of IOL classification using routinely collected obstetric data. RESULTS A 10 group classification system was developed. Of all maternities, 25.4% were induced. Nulliparous and parous women without a prior CS at 39-40 weeks gestation with a singleton cephalic-presenting fetus were the largest groups (21.2% and 24.5% respectively) and accounted for the highest proportion of all IOL (20.7% and 21.5% respectively). The highest within group IOL rates were for nullipara (53.8%) and multipara (45.5%) ≥41 weeks gestation. CONCLUSION We propose a classification system for IOL that has the attributes of simplicity and clarity, utilises information that is readily and reliably collected and reported, and enables standard characterisation of populations of women having an IOL.NHMRC 1021025, ARC FT12010006

Population assessment of future trajectories in coronary heart disease mortality.

Background: Coronary heart disease (CHD) mortality rates have been decreasing in Iceland since the 1980s, largely reflecting improvements in cardiovascular risk factors. The purpose of this study was to predict future CHD mortality in Iceland based on potential risk factor trends. Methods and findings: The previously validated IMPACT model was used to predict changes in CHD mortality between 2010 and 2040 among the projected population of Iceland aged 25–74. Calculations were based on combining: i) data on population numbers and projections (Statistics Iceland), ii) population risk factor levels and projections (Refine Reykjavik study), and iii) effectiveness of specific risk factor reductions (published meta-analyses). Projections for three contrasting scenarios were compared: 1) If the historical risk factor trends of past 30 years were to continue, the declining death rates of past decades would level off, reflecting population ageing. 2) If recent trends in risk factors (past 5 years) continue, this would result in a death rate increasing from 49 to 70 per 100,000. This would reflect a recent plateau in previously falling cholesterol levels and recent rapid increases in obesity and diabetes prevalence. 3) Assuming that in 2040 the entire population enjoys optimal risk factor levels observed in low risk cohorts, this would prevent almost all premature CHD deaths before 2040. Conclusions: The potential increase in CHD deaths with recent trends in risk factor levels is alarming both for Iceland and probably for comparable Western populations. However, our results show considerable room for reducing CHD mortality. Achieving the best case scenario could eradicate premature CHD deaths by 2040. Public health policy interventions based on these predictions may provide a cost effective means of reducing CHD mortality in the future

Mathieu twining characters for K3

The analogue of the McKay-Thompson series for the proposed Mathieu group action on the elliptic genus of K3 is analysed. The corresponding NS-sector twining characters have good modular properties and satisfy remarkable replication identities. These observations provide strong support for the conjecture that the elliptic genus of K3 carries indeed an action of the Mathieu group M24.Comment: 19 page

Access to primary care for socio-economically disadvantaged older people in rural areas: a qualitative study

Objective: We aim to explore the barriers to accessing primary care for socio-economically disadvantaged older people in rural areas. Methods: Using a community recruitment strategy, fifteen people over 65 years, living in a rural area, and receiving financial support were recruited for semi-structured interviews. Four focus groups were held with rural health professionals. Interviews and focus groups were audio-recorded and transcribed. Thematic analysis was used to identify barriers to primary care access. Findings: Older people’s experience can be understood within the context of a patient perceived set of unwritten rules or social contract – an individual is careful not to bother the doctor in return for additional goodwill when they become unwell. However, most found it difficult to access primary care due to engaged telephone lines, availability of appointments, interactions with receptionists; breaching their perceived social contract. This left some feeling unwelcome, worthless or marginalised, especially those with high expectations of the social contract or limited resources, skills and/or desire to adapt to service changes Health professionals’ described how rising demands and expectations coupled with service constraints had necessitated service development, such as fewer home visits, more telephone consultations, triaging calls and modifying the appointment system. Conclusion: Multiple barriers to accessing primary care exist for this group. As primary care is re-organised to reduce costs, commissioners and practitioners must not lose sight of the perceived social contract and models of care that form the basis of how many older people interact with the service

Vacuum Stability, Perturbativity, and Scalar Singlet Dark Matter

We analyze the one-loop vacuum stability and perturbativity bounds on a singlet extension of the Standard Model (SM) scalar sector containing a scalar dark matter candidate. We show that the presence of the singlet-doublet quartic interaction relaxes the vacuum stability lower bound on the SM Higgs mass as a function of the cutoff and lowers the corresponding upper bound based on perturbativity considerations. We also find that vacuum stability requirements may place a lower bound on the singlet dark matter mass for given singlet quartic self coupling, leading to restrictions on the parameter space consistent with the observed relic density. We argue that discovery of a light singlet scalar dark matter particle could provide indirect information on the singlet quartic self-coupling.Comment: 25 pages, 10 figures; v2 - fixed minor typos; v3 - added to text discussions of other references, changed coloring of figures for easier black and white viewin

Incorporating scale dependence in disease burden estimates:the case of human African trypanosomiasis in Uganda

The WHO has established the disability-adjusted life year (DALY) as a metric for measuring the burden of human disease and injury globally. However, most DALY estimates have been calculated as national totals. We mapped spatial variation in the burden of human African trypanosomiasis (HAT) in Uganda for the years 2000-2009. This represents the first geographically delimited estimation of HAT disease burden at the sub-country scale.Disability-adjusted life-year (DALY) totals for HAT were estimated based on modelled age and mortality distributions, mapped using Geographic Information Systems (GIS) software, and summarised by parish and district. While the national total burden of HAT is low relative to other conditions, high-impact districts in Uganda had DALY rates comparable to the national burden rates for major infectious diseases. The calculated average national DALY rate for 2000-2009 was 486.3 DALYs/100 000 persons/year, whereas three districts afflicted by rhodesiense HAT in southeastern Uganda had burden rates above 5000 DALYs/100 000 persons/year, comparable to national GBD 2004 average burden rates for malaria and HIV/AIDS.These results provide updated and improved estimates of HAT burden across Uganda, taking into account sensitivity to under-reporting. Our results highlight the critical importance of spatial scale in disease burden analyses. National aggregations of disease burden have resulted in an implied bias against highly focal diseases for which geographically targeted interventions may be feasible and cost-effective. This has significant implications for the use of DALY estimates to prioritize disease interventions and inform cost-benefit analyses

Bayesian Methods for Exoplanet Science

Exoplanet research is carried out at the limits of the capabilities of current telescopes and instruments. The studied signals are weak, and often embedded in complex systematics from instrumental, telluric, and astrophysical sources. Combining repeated observations of periodic events, simultaneous observations with multiple telescopes, different observation techniques, and existing information from theory and prior research can help to disentangle the systematics from the planetary signals, and offers synergistic advantages over analysing observations separately. Bayesian inference provides a self-consistent statistical framework that addresses both the necessity for complex systematics models, and the need to combine prior information and heterogeneous observations. This chapter offers a brief introduction to Bayesian inference in the context of exoplanet research, with focus on time series analysis, and finishes with an overview of a set of freely available programming libraries.Comment: Invited revie