The future of biomolecular simulation in the pharmaceutical industry: what we can learn from aerodynamics modelling and weather prediction. Part 1. understanding the physical and computational complexity of in silico drug design

The predictive power of simulation has become embedded in the infrastructure of modern economies. Computer-aided design is ubiquitous throughout industry. In aeronautical engineering, built infrastructure and materials manufacturing, simulations are routinely used to compute the performance of potential designs before construction. The ability to predict the behaviour of products is a driver of innovation by reducing the cost barrier to new designs, but also because radically novel ideas can be piloted with relatively little risk. Accurate weather forecasting is essential to guide domestic and military flight paths, and therefore the underpinning simulations are critical enough to have implications for national security. However, in the pharmaceutical and biotechnological industries, the application of computer simulations remains limited by the capabilities of the technology with respect to the complexity of molecular biology and human physiology. Over the last 30 years, molecular-modelling tools have gradually gained a degree of acceptance in the pharmaceutical industry. Drug discovery has begun to benefit from physics-based simulations. While such simulations have great potential for improved molecular design, much scepticism remains about their value. The motivations for such reservations in industry and areas where simulations show promise for efficiency gains in preclinical research are discussed. In this, the first of two complementary papers, the scientific and technical progress that needs to be made to improve the predictive power of biomolecular simulations, and how this might be achieved, is firstly discussed (Part 1). In Part 2, the status of computer simulations in pharma is contrasted with aerodynamics modelling and weather forecasting, and comments are made on the cultural changes needed for equivalent computational technologies to become integrated into life-science industries

The future of biomolecular simulation in the pharmaceutical industry: what we can learn from aerodynamics modelling and weather prediction. Part 1. understanding the physical and computational complexity of in silico drug design

The predictive power of simulation has become embedded in the infrastructure of modern economies. Computer-aided design is ubiquitous throughout industry. In aeronautical engineering, built infrastructure and materials manufacturing, simulations are routinely used to compute the performance of potential designs before construction. The ability to predict the behaviour of products is a driver of innovation by reducing the cost barrier to new designs, but also because radically novel ideas can be piloted with relatively little risk. Accurate weather forecasting is essential to guide domestic and military flight paths, and therefore the underpinning simulations are critical enough to have implications for national security. However, in the pharmaceutical and biotechnological industries, the application of computer simulations remains limited by the capabilities of the technology with respect to the complexity of molecular biology and human physiology. Over the last 30 years, molecular-modelling tools have gradually gained a degree of acceptance in the pharmaceutical industry. Drug discovery has begun to benefit from physics-based simulations. While such simulations have great potential for improved molecular design, much scepticism remains about their value. The motivations for such reservations in industry and areas where simulations show promise for efficiency gains in preclinical research are discussed. In this, the first of two complementary papers, the scientific and technical progress that needs to be made to improve the predictive power of biomolecular simulations, and how this might be achieved, is firstly discussed (Part 1). In Part 2, the status of computer simulations in pharma is contrasted with aerodynamics modelling and weather forecasting, and comments are made on the cultural changes needed for equivalent computational technologies to become integrated into life-science industries

Relationship between fibroblastic foci profusion and high resolution CT morphology in fibrotic lung disease

Background Fibroblastic foci profusion on histopathology and severity of traction bronchiectasis on highresolution computed tomography (HRCT) have been shown to be predictors of mortality in patients with idiopathic pulmonary fibrosis (IPF). The aim of this study was to investigate the relationship between fibroblastic foci (FF) profusion and HRCT patterns in patients with a histopathologic diagnosis of usual interstitial pneumonia (UIP), fibrotic non-specific interstitial pneumonia (NSIP) and chronic hypersensitivity pneumonitis (CHP). Methods The HRCT scans of 162 patients with a histopathologic diagnosis of UIP or fibrotic NSIP (n = 162) were scored on extent of groundglass opacification, reticulation, honeycombing, emphysema and severity of traction bronchiectasis. For each patient, a fibroblastic foci profusion score based on histopathologic appearances was assigned. Relationships between extent of fibroblastic foci and individual HRCT patterns were investigated using univariate correlation analysis and multivariate linear regression. Results Increasing extent of reticulation (P < 0.0001) and increasing severity of traction bronchiectasis (P < 0.0001) were independently associated with increasing FF score within the entire cohort. Within individual multidisciplinary team diagnosis subgroups, the only significant independent association with FF score was severity of traction bronchiectasis in patients with idiopathic pulmonary fibrosis (IPF)/UIP (n = 66, r2 = 0.19, P < 0.0001) and patients with chronic hypersensitivity pneumonitis (CHP) (n = 49, r2 = 0.45, P < 0.0001). Furthermore, FF score had the strongest association with severity of traction bronchiectasis in patients with IPF (r2 = 0.34, P < 0.0001) and CHP (r2 = 0.35, P < 0.0001). There was no correlation between FF score and severity of traction bronchiectasis in patients with fibrotic NSIP. Global disease extent had the strongest association with severity of traction bronchiectasis in patients with fibrotic NSIP (r2 = 0.58, P < 0.0001). Conclusion In patients with fibrotic lung disease, profusion of fibroblastic foci is strikingly related to the severity of traction bronchiectasis, particularly in IPF and CHP. This may explain the growing evidence that traction bronchiectasis is a predictor of mortality in several fibrotic lung diseases

Are Ethnic and Gender Specific Equations Needed to Derive Fat Free Mass from Bioelectrical Impedance in Children of South Asian, Black African-Caribbean and White European Origin? Results of the Assessment of Body Composition in Children Study

Background Bioelectrical impedance analysis (BIA) is a potentially valuable method for assessing lean mass and body fat levels in children from different ethnic groups. We examined the need for ethnic- and gender-specific equations for estimating fat free mass (FFM) from BIA in children from different ethnic groups and examined their effects on the assessment of ethnic differences in body fat. Methods Cross-sectional study of children aged 8–10 years in London Primary schools including 325 South Asians, 250 black African-Caribbeans and 289 white Europeans with measurements of height, weight and arm-leg impedance (Z; Bodystat 1500). Total body water was estimated from deuterium dilution and converted to FFM. Multilevel models were used to derive three types of equation {A: FFM = linear combination(height+weight+Z); B: FFM = linear combination(height2/Z); C: FFM = linear combination(height2/Z+weight)}. Results Ethnicity and gender were important predictors of FFM and improved model fit in all equations. The models of best fit were ethnicity and gender specific versions of equation A, followed by equation C; these provided accurate assessments of ethnic differences in FFM and FM. In contrast, the use of generic equations led to underestimation of both the negative South Asian-white European FFM difference and the positive black African-Caribbean-white European FFM difference (by 0.53 kg and by 0.73 kg respectively for equation A). The use of generic equations underestimated the positive South Asian-white European difference in fat mass (FM) and overestimated the positive black African-Caribbean-white European difference in FM (by 4.7% and 10.1% respectively for equation A). Consistent results were observed when the equations were applied to a large external data set. Conclusions Ethnic- and gender-specific equations for predicting FFM from BIA provide better estimates of ethnic differences in FFM and FM in children, while generic equations can misrepresent these ethnic differences

Impact of patient global assessment on achieving remission in patients with rheumatoid arthritis: A multinational study using the METEOR database

OBJECTIVE: There is an ongoing debate about excluding patient's global assessment (PtGA) from composite and Boolean-based definitions of rheumatoid arthritis (RA) remission. This study aimed at determining the influence of PtGA on RA disease states, exploring differences across countries, and understanding the association between PtGA, measures of disease impact (symptoms), and markers of disease activity (inflammation). METHODS: Cross-sectional data from the Measurement of Efficacy of Treatment in the Era of Outcome in Rheumatology international database were used. We calculated the proportion of patients failing American College of Rheumatology/European League Against Rheumatism Boolean-based remission (4-variable remission) solely due to PtGA (PtGA-near-remission) in the overall sample and in the most representative countries (i.e., those with >3,000 patients in the database). Multivariable linear regression models were used to identify the main determinants of PtGA, grouped in predominantly inflammatory impact factors (28 tender joint counts, 28 swollen joint counts, and C-reactive protein level) and disease impact factors (pain and function). RESULTS: This study included 27,768 patients. Excluding PtGA from the Boolean-based definition (3-variable remission) increased the remission rate from 5.8% to 15.8%. The rate of PtGA-near-remission varied considerably between countries, from 1.7% in India to 17.9% in Portugal. One-third of the patients in PtGA-near-remission group scored PtGA >4 of 10. Pain and function were the main correlates of PtGA, with inflammation-related variables contributing less to the model (R2 = 0.57). CONCLUSION: PtGA is moderately related to joint inflammation overall, but only weakly so in low levels of disease activity. A considerable proportion of patients otherwise in biologic remission still perceive high PtGA, putting them at risk of excessive immunosuppressive treatment

California Current seascape influences juvenile salmon foraging ecology at multiple scales

Juvenile salmon Oncorhynchus spp. experience variable mortality rates during their first few months in the ocean, and high growth during this period is critical to minimize size selective predation. Examining links between the physical environment and foraging ecology is important to understand mechanisms that drive growth. These mechanisms are complex and include interactions among the physical environment, forage availability, bioenergetics, and salmon foraging behavior. Our objectives were to explore how seascape features (biological and physical) influence juvenile Chinook salmon O. tshawytscha foraging at annual and feedingevent scales in the California Current Ecosystem. We demonstrate that forage abundance was the most influential determinant of mean salmon stomach fullness at the annual scale, while at the feeding-event scale, fullness increased with greater cumulative upwelling during the 10 d prior and at closer distances to thermal fronts. Upwelling promotes nutrient enrichment and productivity, while fronts concentrate organisms, likely resulting in available prey to salmon and increased stomach fullness. Salmon were also more likely to consume krill when there was high prior upwelling,andswitchedtonon-krillinvertebrates(i.e.amphipods,decapods,copepods)inweaker upwelling conditions. As salmon size increased from 72−250 mm, salmon were more likely to consume fish, equal amounts of krill, and fewer non-krill invertebrates. Broad seascape processes determined overall prey availability and fullness in a given year, while fine- and meso-scale processes influenced local accessibility of prey to individual salmon. Therefore, processes occurring at multiple scales will influence how marine organisms respond to changing environment

Temperature stability of thin film refractory plasmonic materials

Materials such as W, TiN, and SrRuO3 (SRO) have been suggested as promising alternatives to Au and Ag in plasmonic applications owing to their stability at high operational temperatures. However, investigation of the reproducibility of the optical properties after thermal cycling between room and elevated temperatures is so far lacking. Here, thin films of W, Mo, Ti, TiN, TiON, Ag, Au, SrRuO3 and SrNbO3 are investigated to assess their viability for robust refractory plasmonic applications. These results are further compared to the performance of SrMoO3 reported in literature. Films ranging in thickness from 50 to 105 nm are deposited on MgO, SrTiO3 and Si substrates by e-beam evaporation, RF magnetron sputtering and pulsed laser deposition, prior to characterisation by means of AFM, XRD, spectroscopic ellipsometry, and DC resistivity. Measurements are conducted before and after annealing in air at temperatures ranging from 300 to 1000° C for one hour, to establish the maximum cycling temperature and potential longevity at elevated temperatures for each material. It is found that SrRuO3 retains metallic behaviour after annealing at 800° C, while SrNbO3 undergoes a phase transition resulting in a loss of metallic behaviour after annealing at 400° C. Importantly, the optical properties of TiN and TiON are degraded as a result of oxidation and show a loss of metallic behaviour after annealing at 500° C, while the same is not observed in Au until annealing at 600° C. Nevertheless, both TiN and TiON may be better suited than Au or SRO for high temperature applications operating under vacuum conditions

The Search for Invariance: Repeated Positive Testing Serves the Goals of Causal Learning

Positive testing is characteristic of exploratory behavior, yet it seems to be at odds with the aim of information seeking. After all, repeated demonstrations of one’s current hypothesis often produce the same evidence and fail to distinguish it from potential alternatives. Research on the development of scientific reasoning and adult rule learning have both documented and attempted to explain this behavior. The current chapter reviews this prior work and introduces a novel theoretical account—the Search for Invariance (SI) hypothesis—which suggests that producing multiple positive examples serves the goals of causal learning. This hypothesis draws on the interventionist framework of causal reasoning, which suggests that causal learners are concerned with the invariance of candidate hypotheses. In a probabilistic and interdependent causal world, our primary goal is to determine whether, and in what contexts, our causal hypotheses provide accurate foundations for inference and intervention—not to disconfirm their alternatives. By recognizing the central role of invariance in causal learning, the phenomenon of positive testing may be reinterpreted as a rational information-seeking strategy