Carbon-enhanced metal-poor stars in the SDSS-APOGEE data base

We identify six new carbon-enhanced metal-poor (CEMP) stars ([C/Fe]>+ 0.7 and [Fe/H] < -1.8) and another seven likely candidates within the APOGEE data base following Data Release 12. These stars have chemical compositions typical of metal-poor halo stars, e.g. mean [a/Fe]=+0.24 +/- 0.24, based on the APOGEE Stellar Parameters and Chemical Abundances Pipeline results. A lack of heavy-element spectral lines impedes further sub-classification of these CEMP stars, however, based on radial velocity (RV) scatter, we predict most are not CEMP-s stars which are typically found in binary systems. Only one object, 2M15312547+4220551, may be in a binary since it exhibits a scatter in its RV of 1.7 +/- 0.6 km s(-1) based on three visits over a 25.98 d baseline. Optical observations are now necessary to confirm the stellar parameters and low metallicities of these stars, to determine the heavy-element abundance ratios and improve the precision in the derived abundances, and to examine their CEMP sub-classifications

Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria

Associating mutations causing cystinuria with disease severity with the aim of providing precision medicine

Background Cystinuria is an inherited disease that results in the formation of cystine stones in the kidney, which can have serious health complications. Two genes (SLC7A9 and SLC3A1) that form an amino acid transporter are known to be responsible for the disease. Variants that cause the disease disrupt amino acid transport across the cell membrane, leading to the build-up of relatively insoluble cystine, resulting in formation of stones. Assessing the effects of each mutation is critical in order to provide tailored treatment options for patients. We used various computational methods to assess the effects of cystinuria associated mutations, utilising information on protein function, evolutionary conservation and natural population variation of the two genes. We also analysed the ability of some methods to predict the phenotypes of individuals with cystinuria, based on their genotypes, and compared this to clinical data. Results Using a literature search, we collated a set of 94 SLC3A1 and 58 SLC7A9 point mutations known to be associated with cystinuria. There are differences in sequence location, evolutionary conservation, allele frequency, and predicted effect on protein function between these mutations and other genetic variants of the same genes that occur in a large population. Structural analysis considered how these mutations might lead to cystinuria. For SLC7A9, many mutations swap hydrophobic amino acids for charged amino acids or vice versa, while others affect known functional sites. For SLC3A1, functional information is currently insufficient to make confident predictions but mutations often result in the loss of hydrogen bonds and largely appear to affect protein stability. Finally, we showed that computational predictions of mutation severity were significantly correlated with the disease phenotypes of patients from a clinical study, despite different methods disagreeing for some of their predictions. Conclusions The results of this study are promising and highlight the areas of research which must now be pursued to better understand how mutations in SLC3A1 and SLC7A9 cause cystinuria. The application of our approach to a larger data set is essential, but we have shown that computational methods could play an important role in designing more effective personalised treatment options for patients with cystinuria

The secret to successful deep-sea invasion: does low temperature hold the key?

There is a general consensus that today’s deep-sea biodiversity has largely resulted from recurrent invasions and speciations occurring through homogenous waters during periods of the Phanerozoic eon. Migrations likely continue today, primarily via isothermal water columns, such as those typical of Polar Regions, but the necessary ecological and physiological adaptations behind them are poorly understood. In an evolutionary context, understanding the adaptations, which allow for colonisation to high-pressure environments, may enable us to predict future events. In this investigation, we examine pressure tolerance during development, in the shallow-water neogastropod Buccinum undatum using thermally acclimated egg masses from temperate and sub-polar regions across the species range. Fossil records indicate neogastropods to have a deep-water origin, suggesting shallow-water species may be likely candidates for re-emergence into the deep sea. Our results show population level differences in physiological thresholds, which indicate low temperature acclimation to increase pressure tolerance. These findings imply this species is capable of deep-sea penetration through isothermal water columns prevailing at high latitudes. This study gives new insight into the fundamentals behind past and future colonisation events. Such knowledge is instrumental to understand better how changes in climate envelopes affect the distribution and radiation of species both along latitudinal as well as bathymetric temperature gradients

Cost and outcome of behavioural activation versus cognitive behaviour therapy for depression (COBRA): study protocol for a randomised controlled trial.

BACKGROUND: Cognitive behaviour therapy (CBT) is an effective treatment for depression. However, CBT is a complex therapy that requires highly trained and qualified practitioners, and its scalability is therefore limited by the costs of training and employing sufficient therapists to meet demand. Behavioural activation (BA) is a psychological treatment for depression that may be an effective alternative to CBT and, because it is simpler, might also be delivered by less highly trained and specialised mental health workers. METHODS/DESIGN: COBRA is a two-arm, non-inferiority, patient-level randomised controlled trial, including clinical, economic, and process evaluations comparing CBT delivered by highly trained professional therapists to BA delivered by junior professional or para-professional mental health workers to establish whether the clinical effectiveness of BA is non-inferior to CBT and if BA is cost effective compared to CBT. Four hundred and forty patients with major depressive disorder will be recruited through screening in primary care. We will analyse for non-inferiority in per-protocol and intention-to-treat populations. Our primary outcome will be severity of depression symptoms (Patient Health Questionnaire-9) at 12 months follow-up. Secondary outcomes will be clinically significant change and severity of depression at 18 months, and anxiety (General Anxiety Disorder-7 questionnaire) and health-related quality of life (Short-Form Health Survey-36) at 12 and 18 months. Our economic evaluation will take the United Kingdom National Health Service/Personal Social Services perspective to include costs of the interventions, health and social care services used, plus productivity losses. Cost-effectiveness will explored in terms of quality-adjusted life years using the EuroQol-5D measure of health-related quality of life. DISCUSSION: The clinical and economic outcomes of this trial will provide the evidence to help policy makers, clinicians and guideline developers decide on the merits of including BA as a first-line treatment of depression. TRIAL REGISTRATION: Current Controlled Trials ISRCTN27473954