Mixing thermodynamics and photocatalytic properties of GaP-ZnS solid solutions

Preparation of solid solutions represents an effective means to improve the photocatalytic properties of semiconductor-based materials. Nevertheless, the effects of site-occupancy disorder on the mixing stability and electronic properties of the resulting compounds are difficult to predict and consequently many experimental trials may be required before achieving enhanced photocatalytic activity. Here, we employ first-principles methods based on density functional theory to estimate the mixing free energy and the structural and electronic properties of (GaP)x(ZnS)1-x solid solutions, a representative semiconductor-based optoelectronic material. Our method relies on a multi-configurational supercell approach that takes into account the configurational and vibrational contributions to the free energy. Phase competition among the zinc-blende and wurtzite polymorphs is also considered. We demonstrate overall excellent agreement with the available experimental data: (1) zinc-blende emerges as the energetically most favorable phase, (2) the solid solution energy band gap lies within the 2-3 eV range for all compositions, and (3) the energy band gap of the solid solution is direct for compositions x < 75%. We find that at ambient conditions most (GaP)x(ZnS)1-x solid solutions are slightly unstable against decomposition into GaP- and ZnS-rich regions. Nevertheless, compositions x = 25, 50, and 75% render robust metastable states that owing to their favorable energy band gaps and band levels relative to vacuum are promising hydrogen evolution photocatalysts for water splitting under visible light. The employed theoretical approach provides valuable insights into the physicochemical properties of potential solid-solution photocatalysts and offers useful guides for their experimental realization

Adventures in boron chemistry – the prediction of novel ultra-flexible boron oxide frameworks

We predict a wide range of ultra-flexible low-energy forms of boron oxides in which rigid B–O–B bridges link boron–oxygen heterocycles.</p

River Flows and Water Wars: Emerging Science for Environmental Decision Making

Real and apparent conflicts between ecosystem and human needs for fresh water are contributing to the emergence of an alternative model for conducting river science around the world. The core of this new paradigm emphasizes the need to forge new partnerships between scientists and other stakeholders where shared ecological goals and river visions are developed, and the need for new experimental approaches to advance scientific understanding at the scales relevant to whole-river management. We identify four key elements required to make this model succeed: existing and planned water projects represent opportunities to conduct ecosystem-scale experiments through controlled river flow manipulations; more cooperative interactions among scientists, managers, and other stakeholders are critical; experimental results must be synthesized across studies to allow broader generalization; and new, innovative funding partnerships are needed to engage scientists and to broadly involve the government, the private sector, and NGOs

Triple-Negative Breast Cancer Risk Genes Identified by Multigene Hereditary Cancer Panel Testing

Background: Germline genetic testing with hereditary cancer gene panels can identify women at increased risk of breast cancer. However, those at increased risk of triple-negative (estrogen receptor-negative, progesterone receptor-negative, human epidermal growth factor receptor-negative) breast cancer (TNBC) cannot be identified because predisposition genes for TNBC, other than BRCA1, have not been established. The aim of this study was to define the cancer panel genes associated with increased risk of TNBC. Methods: Multigene panel testing for 21 genes in 8753 TNBC patients was performed by a clinical testing laboratory, and testing for 17 genes in 2148 patients was conducted by a Triple Negative Breast Cancer Consortium(TNBCC) of research studies. Associations between deleterious mutations in cancer predisposition genes and TNBC were evaluated using results from TNBC patients and reference controls. Results: Germline pathogenic variants in BARD1, BRCA1, BRCA2, PALB2, and RAD51D were associated with high risk (odds ratio > 5.0) of TNBC and greater than 20% lifetime risk for overall breast cancer among Caucasians. Pathogenic variants in BRIP1, RAD51C, and TP53 were associated with moderate risk (odds ratio > 2) of TNBC. Similar trends were observed for the African American population. Pathogenic variants in these TNBC genes were detected in 12.0% (3.7% non-BRCA1/2) of all participants. Conclusions: Multigene hereditary cancer panel testing can identify women with elevated risk of TNBC due to mutations in BARD1, BRCA1, BRCA2, PALB2, and RAD51D. These women can potentially benefit from improved screening, risk management, and cancer prevention strategies. Patients with mutations may also benefit from specific targeted therapeutic strategies.Peer reviewe

BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

Background: The K3326X variant in BRCA2 (BRCA2*c.9976A&gt;T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

From Sensor Data to Animal Behaviour: An Oystercatcher Example

Animal-borne sensors enable researchers to remotely track animals, their physiological state and body movements. Accelerometers, for example, have been used in several studies to measure body movement, posture, and energy expenditure, although predominantly in marine animals. In many studies, behaviour is often inferred from expert interpretation of sensor data and not validated with direct observations of the animal. The aim of this study was to derive models that could be used to classify oystercatcher (Haematopus ostralegus) behaviour based on sensor data. We measured the location, speed, and tri-axial acceleration of three oystercatchers using a flexible GPS tracking system and conducted simultaneous visual observations of the behaviour of these birds in their natural environment. We then used these data to develop three supervised classification trees of behaviour and finally applied one of the models to calculate time-activity budgets. The model based on accelerometer data developed to classify three behaviours (fly, terrestrial locomotion, and no movement) was much more accurate (cross-validation error = 0.14) than the model based on GPS-speed alone (cross-validation error = 0.35). The most parsimonious acceleration model designed to classify eight behaviours could distinguish five: fly, forage, body care, stand, and sit (cross-validation error = 0.28); other behaviours that were observed, such as aggression or handling of prey, could not be distinguished. Model limitations and potential improvements are discussed. The workflow design presented in this study can facilitate model development, be adapted to a wide range of species, and together with the appropriate measurements, can foster the study of behaviour and habitat use of free living animals throughout their annual routine