Red Giant Eclipsing Binaries: Exploring Non-Oscillators and Testing Asteroseismic Scalings

Thanks to advances in asteroseismology, red giants have become astrophysical laboratories for probing the Milky Way. Eclipsing binaries allow us to directly measure stellar properties independently of asteroseismology, which we use to investigate why some red giants don't oscillate and test asteroseismic scaling relations for those that do. By combining orbital solutions, high-resolution spectroscopy, and stellar evolution models for a subset of eight eclipsing red giants observed by Kepler, we find short-period binaries with strong tidal forces and systems with active red giants are less likely to exhibit solar-like oscillations. We also preview the results from Gaulme et al. 2016 (submitted). We find asteroseismic scalings overestimate red giant radii by about 6% on average and masses by about 16% in ten systems observed by Kepler. Systematic overestimation of mass leads to underestimation of stellar age, which has important implications for ensemble asteroseismology applied to galactic studies

Do palliative care patients and relatives think it would be acceptable to use Bispectral index (BIS) technology to monitor palliative care patients' levels of consciousness? A qualitative exploration with interviews and focus groups for the I-CAN-CARE research programme

BACKGROUND: Bispectral index (BIS) monitoring uses electroencephalographic data as an indicator of patients' consciousness level. This technology might be a useful adjunct to clinical observation when titrating sedative medications for palliative care patients. However, the use of BIS in palliative care generally, and in the UK in particular, is under-researched. A key area is this technology's acceptability for palliative care service users. Ahead of trialling BIS in practice, and in order to ascertain whether such a trial would be reasonable, we conducted a study to explore UK palliative care patients' and relatives' perceptions of the technology, including whether they thought its use in palliative care practice would be acceptable. METHODS: A qualitative exploration was undertaken. Participants were recruited through a UK hospice. Focus groups and semi-structured interviews were conducted with separate groups of palliative care patients, relatives of current patients, and bereaved relatives. We explored their views on acceptability of using BIS with palliative care patients, and analysed their responses following the five key stages of the Framework method. RESULTS: We recruited 25 participants. There were ten current hospice patients in three focus groups, four relatives of current patients in one focus group and one individual interview, and eleven bereaved relatives in three focus groups and two individual interviews. Our study participants considered BIS acceptable for monitoring palliative care patients' consciousness levels, and that it might be of use in end-of-life care, provided that it was additional to (rather than a replacement of) usual care, and patients and/or family members were involved in decisions about its use. Participants also noted that BIS, while possibly obtrusive, is not invasive, with some seeing it as equivalent to wearable technological devices such as activity watches. CONCLUSIONS: Participants considered BIS technology might be of benefit to palliative care as a non-intrusive means of assisting clinical assessment and decision-making at the end of life, and concluded that it would therefore be acceptable to trial the technology with patients

Identification of pain indicators for infants at risk for neurological impairment: A Delphi consensus study

BACKGROUND: A number of infant pain measures have been developed over the past 15 years incorporating behavioural and physiologic indicators; however, no reliable or valid measure exists for infants who are at risk for neurological impairments (NI). The objective of this study was to establish consensus about which behavioural, physiologic and contextual indicators best characterize pain in infants at high, moderate and low levels of risk for NI. METHODS: A 39- item, self-administered electronic survey that included infant physiologic, behavioral and contextual pain indicators was used in a two round Delphi consensus exercise. Fourteen pediatric pain experts were polled individually and anonymously on the importance and usefulness of the pain indicators for the 3 differing levels of risk for NI. RESULTS: The strength of agreement between expert raters was moderate in Round 1 and fair in Round 2. In general, pain indicators with the highest concordance for all three groups were brow bulge, facial grimace, eye squeeze, and inconsolability. Increased heart rate from baseline in the moderate and severe groups demonstrated high concordance. In the severe risk group, fluctuations in heart rate and reduced oxygen saturation were also highly rated. CONCLUSION: These data constitute the first step in contributing to the development and validation of a pain measure for infants at risk for NI. In future research, we will integrate these findings with the opinions of (a) health care providers about the importance and usefulness of infant pain indicators and (b) the pain responses of infants at mild, moderate and high risk for NI

Feature Fusion of Raman Chemical Imaging and Digital Histopathology using Machine Learning for Prostate Cancer Detection

The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accurate diagnosis can directly benefit a patient's quality of life and prognosis. Towards addressing this issue, we present a learning model for the automatic identification of prostate cancer. While many prostate cancer studies have adopted Raman spectroscopy approaches, none have utilised the combination of Raman Chemical Imaging (RCI) and other imaging modalities. This study uses multimodal images formed from stained Digital Histopathology (DP) and unstained RCI. The approach was developed and tested on a set of 178 clinical samples from 32 patients, containing a range of non-cancerous, Gleason grade 3 (G3) and grade 4 (G4) tissue microarray samples. For each histological sample, there is a pathologist labelled DP - RCI image pair. The hypothesis tested was whether multimodal image models can outperform single modality baseline models in terms of diagnostic accuracy. Binary non-cancer/cancer models and the more challenging G3/G4 differentiation were investigated. Regarding G3/G4 classification, the multimodal approach achieved a sensitivity of 73.8% and specificity of 88.1% while the baseline DP model showed a sensitivity and specificity of 54.1% and 84.7% respectively. The multimodal approach demonstrated a statistically significant 12.7% AUC advantage over the baseline with a value of 85.8% compared to 73.1%, also outperforming models based solely on RCI and median Raman spectra. Feature fusion of DP and RCI does not improve the more trivial task of tumour identification but does deliver an observed advantage in G3/G4 discrimination. Building on these promising findings, future work could include the acquisition of larger datasets for enhanced model generalization.Comment: 19 pages, 8 tables, 18 figure

Feature Fusion of Raman Chemical Imaging and Digital Histopathology using Machine Learning for Prostate Cancer Detection

The diagnosis of prostate cancer is challenging due to the heterogeneity of its presentations, leading to the over diagnosis and treatment of non-clinically important disease. Accurate diagnosis can directly benefit a patient’s quality of life and prognosis. Towards addressing this issue, we present a learning model for the automatic identification of prostate cancer. While many prostate cancer studies have adopted Raman spectroscopy approaches, none have utilised the combination of Raman Chemical Imaging (RCI) and other imaging modalities. This study uses multimodal images formed from stained Digital Histopathology (DP) and unstained RCI. The approach was developed and tested on a set of 178 clinical samples from 32 patients, containing a range of non-cancerous, Gleason grade 3 (G3) and grade 4 (G4) tissue microarray samples. For each histological sample, there is a pathologist labelled DP - RCI image pair. The hypothesis tested was whether multimodal image models can outperform single modality baseline models in terms of diagnostic accuracy. Binary non-cancer/cancer models and the more challenging G3/G4 differentiation were investigated. Regarding G3/G4 classification, the multimodal approach achieved a sensitivity of 73.8% and specificity of 88.1% while the baseline DP model showed a sensitivity and specificity of 54.1% and 84.7% respectively. The multimodal approach demonstrated a statistically significant 12.7% AUC advantage over the baseline with a value of 85.8% compared to 73.1%, also outperforming models based solely on RCI and median Raman spectra. Feature fusion of DP and RCI does not improve the more trivial task of tumour identification but does deliver an observed advantage in G3/G4 discrimination. Building on these promising findings, future work could include the acquisition of larger datasets for enhanced model generalization

Synthesis and biological evaluation of N-cyanoalkyl-, Naminoalkyl-, and N-guanidinoalkyl-substituted 4-aminoquinoline derivatives as potent, selective, brain permeable antitrypanosomal agents

YesCurrent drugs against human African trypanosomiasis (HAT) suffer from several serious drawbacks. The search for novel, effective, brain permeable, safe, and inexpensive antitrypanosomal compounds is therefore an urgent need. We have recently reported that the 4-aminoquinoline derivative huprine Y, developed in our group as an anticholinesterasic agent, exhibits a submicromolar potency against Trypanosoma brucei and that its homo- and hetero-dimerization can result in to up to three-fold increased potency and selectivity. As an alternative strategy towards more potent smaller molecule anti-HAT agents, we have explored the introduction of ω-cyanoalkyl, ω-aminoalkyl, or ω-guanidinoalkyl chains at the primary amino group of huprine or the simplified 4-aminoquinoline analogue tacrine. Here, we describe the evaluation of a small in-house library and a second generation of newly synthesized derivatives, which has led to the identification of 13 side chain modified 4-aminoquinoline derivatives with submicromolar potencies against T. brucei. Among these compounds, the guanidinononyltacrine analogue 15e exhibits a 5-fold increased antitrypanosomal potency, 10-fold increased selectivity, and 100-fold decreased anticholinesterasic activity relative to the parent huprine Y. Its biological profile, lower molecular weight relative to dimeric compounds, reduced lipophilicity, and ease of synthesis, make it an interesting anti-HAT lead, amenable to further optimization to eliminate its remaining anticholinesterasic activity.Wellcome Trus

U.S. Billion-ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry

The Report, Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply (generally referred to as the Billion-Ton Study or 2005 BTS), was an estimate of “potential” biomass within the contiguous United States based on numerous assumptions about current and future inventory and production capacity, availability, and technology. In the 2005 BTS, a strategic analysis was undertaken to determine if U.S. agriculture and forest resources have the capability to potentially produce at least one billion dry tons of biomass annually, in a sustainable manner—enough to displace approximately 30% of the country’s present petroleum consumption. To ensure reasonable confidence in the study results, an effort was made to use relatively conservative assumptions. However, for both agriculture and forestry, the resource potential was not restricted by price. That is, all identified biomass was potentially available, even though some potential feedstock would more than likely be too expensive to actually be economically available. In addition to updating the 2005 study, this report attempts to address a number of its shortcoming

Antibiotic research and development: business as usual?

This article contends that poor economic incentives are an important reason for the lack of new drugs and explains how the DRIVE-AB intends to change the landscape by harnessing the expertise, motivation and diversity of its partner