Periodic density functional theory calculations of bulk and the (010) surface of goethite

<p>Abstract</p> <p>Background</p> <p>Goethite is a common and reactive mineral in the environment. The transport of contaminants and anaerobic respiration of microbes are significantly affected by adsorption and reduction reactions involving goethite. An understanding of the mineral-water interface of goethite is critical for determining the molecular-scale mechanisms of adsorption and reduction reactions. In this study, periodic density functional theory (DFT) calculations were performed on the mineral goethite and its (010) surface, using the Vienna <it>Ab Initio </it>Simulation Package (VASP).</p> <p>Results</p> <p>Calculations of the bulk mineral structure accurately reproduced the observed crystal structure and vibrational frequencies, suggesting that this computational methodology was suitable for modeling the goethite-water interface. Energy-minimized structures of bare, hydrated (one H₂O layer) and solvated (three H₂O layers) (010) surfaces were calculated for 1 × 1 and 3 × 3 unit cell slabs. A good correlation between the calculated and observed vibrational frequencies was found for the 1 × 1 solvated surface. However, differences between the 1 × 1 and 3 × 3 slab calculations indicated that larger models may be necessary to simulate the relaxation of water at the interface. Comparison of two hydrated surfaces with molecularly and dissociatively adsorbed H₂O showed a significantly lower potential energy for the former.</p> <p>Conclusion</p> <p>Surface Fe-O and (Fe)O-H bond lengths are reported that may be useful in surface complexation models (SCM) of the goethite (010) surface. These bond lengths were found to change significantly as a function of solvation (i.e., addition of two extra H₂O layers above the surface), indicating that this parameter should be carefully considered in future SCM studies of metal oxide-water interfaces.</p

Beyond the particular and universal:dependence, independence, and interdependence of context, justice, and ethics

This article reflects on context effects in the study of behavioral ethics and organizational justice. After a general overview, we review three key challenges confronting research in these two domains. First, we consider social scientific versus normative approaches to inquiry. The former aims for a scientific description, while the latter aims to provide prescriptive advice for moral conduct. We argue that the social scientific view can be enriched by considering normative paradigms. The next challenge we consider, involves the duality of morally upright versus morally inappropriate behavior. We observe that there is a long tradition of categorizing behavior dichotomously (e.g., good vs. bad) rather than continuously. We conclude by observing that more research is needed to compare the dichotomous versus continuous perspectives. Third, we examine the role of “cold” cognitions and “hot” affect in making judgments of ethicality. Historically speaking, research has empathized cognition, though recent work has begun to add greater balance to affective reactions. We argue that both cognition and affect are important, but more research is needed to determine how they work together. After considering these three challenges, we then turn to our special issue, providing short reviews of each contribution and how they help in better addressing the three challenges we have identified

Antioxidant intake among Brazilian adults - The Brazilian Osteoporosis Study (BRAZOS): a cross-sectional study

<p>Abstract</p> <p>Background</p> <p>Antioxidant nutrient intake and the lesser formation of free radicals seem to contribute to chronic diseases. The aim of the present study was to evaluate the intake profile of the main dietary antioxidants in a representative sample of the adult Brazilian population and discuss the main consequences of a low intake of these micronutrients on overall health.</p> <p>Methods</p> <p>The sample comprised 2344 individuals aged 40 years or older from 150 cities and was based on a probabilistic sample from official data. The research was conducted through in-home interviews administered by a team trained for this purpose. Dietary intake information was obtained through 24-h recall. The Nutrition Data System for Research software program was used to analyze data on the intake of vitamins A, C and E, selenium and zinc, which was compared to Dietary Reference Intakes (DRIs). Differences in intake according to sex, anthropometrics, socioeconomic status and region were also evaluated. The SPSS statistical package (version 13) was used for the statistical analysis. P-values < 0.05 were considered significant.</p> <p>Results</p> <p>Higher proportions of low intake in relation to recommended values were found for vitamin E (99.7%), vitamin A (92.4%) and vitamin C (85.1%) in both genders. Intake variations were found between different regions, which may reflect cultural habits.</p> <p>Conclusion</p> <p>These results should lead to the development of public health policies that encourage educational strategies for improving the intake of micronutrients, which are essential to overall health and prevention of non-communicable diseases.</p

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer’s dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis

Accurate Encoding and Decoding by Single Cells: Amplitude Versus Frequency Modulation

Cells sense external concentrations and, via biochemical signaling, respond by regulating the expression of target proteins. Both in signaling networks and gene regulation there are two main mechanisms by which the concentration can be encoded internally: amplitude modulation (AM), where the absolute concentration of an internal signaling molecule encodes the stimulus, and frequency modulation (FM), where the period between successive bursts represents the stimulus. Although both mechanisms have been observed in biological systems, the question of when it is beneficial for cells to use either AM or FM is largely unanswered. Here, we first consider a simple model for a single receptor (or ion channel), which can either signal continuously whenever a ligand is bound, or produce a burst in signaling molecule upon receptor binding. We find that bursty signaling is more accurate than continuous signaling only for sufficiently fast dynamics. This suggests that modulation based on bursts may be more common in signaling networks than in gene regulation. We then extend our model to multiple receptors, where continuous and bursty signaling are equivalent to AM and FM respectively, finding that AM is always more accurate. This implies that the reason some cells use FM is related to factors other than accuracy, such as the ability to coordinate expression of multiple genes or to implement threshold crossing mechanisms