Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic hydration shell restores Kauzmann's 1959 explanation of how the hydrophobic factor drives protein folding

Significance Kauzmann's proposal that the hydrophobicity of hydrocarbons in water is caused by their hydration shells is modified here by replacing his clathrate water shell with a dynamic shell formed by van der Waals attraction, as proposed by Jorgensen et al. The hydration energetics of alkanes are then shown to be proportional to n, the number of waters in the shell given by the simulations of Jorgensen et al. The Ben-Naim standard state, which is based on solute transfer between fixed positions in the gas and liquid phases, is used for the hydration energetics. Recent experimental evidence for hydration shells is reviewed. Kauzmann's explanation of how the hydrophobic factor drives protein folding is reexamined. His explanation said that hydrocarbon hydration shells are formed, possibly of clathrate water, and they explain why hydrocarbons have uniquely low solubilities in water. His explanation was not universally accepted because of skepticism about the clathrate hydration shell. A revised version is given here in which a dynamic hydration shell is formed by van der Waals (vdw) attraction, as proposed in 1985 by Jorgensen et al. [Jorgensen WL, Gao J, Ravimohan C (1985) J Phys Chem 89:3470–3473]. The vdw hydration shell is implicit in theories of hydrophobicity that contain the vdw interaction between hydrocarbon C and water O atoms. To test the vdw shell model against the known hydration energetics of alkanes, the energetics should be based on the Ben-Naim standard state (solute transfer between fixed positions in the gas and liquid phases). Then the energetics are proportional to n, the number of water molecules correlated with an alkane by vdw attraction, given by the simulations of Jorgensen et al. The energetics show that the decrease in entropy upon hydration is the root cause of hydrophobicity; it probably results from extensive ordering of water molecules in the vdw shell. The puzzle of how hydrophobic free energy can be proportional to nonpolar surface area when the free energy is unfavorable and the only known interaction (the vdw attraction) is favorable, is resolved by finding that the unfavorable free energy is produced by the vdw shell.
Configuration of Continuous Piecewise-Linear Neural Networks

The problem of constructing a general continuous piecewise-linear neural network is considered in this paper. It is shown that every projection domain of an arbitrary continuous piecewise-linear function can be partitioned into convex polyhedra by using difference functions of its local linear functions. Based on these convex polyhedra, a group of continuous piecewise-linear basis functions are formulated. It is proven that a linear combination of these basis functions plus a constant, which we call a standard continuous piecewise-linear neural network, can represent all continuous piecewise-linear functions. In addition, the proposed standard continuous piecewise-linear neural network is applied to solve some function approximation problems. A number of numerical experiments are presented to illustrate that the standard continuous piecewise-linear neural network can be a promising tool for function approximation.
Heavy Metal Exposure in Early Life - Health and Labour Market Perspectives

This thesis consists of three empirical studies on the effects of exposure to heavy metal pollution in early childhood on a broad set of individual outcomes. The first study analyses how accumulated exposure to metal pollution during childhood affects long-run outcomes. Exploiting policy-driven reductions in metal pollution in Sweden, it shows that accumulated exposure to metals (including cadmium, chromium, copper, lead, nickel, vanadium, and zinc) leads to lower GPA scores, fewer years of education, and reduced adult wages. It also shows that these effects may contribute to intergenerational persistence of socioeconomic status due to inequalities in pollution exposure driven by parental sorting.The second study estimates the effect of lead pollution on infant mortality in five Sub-Saharan African countries. A sharp phase-out of leaded gasoline provides exogenous variation in changes in lead pollution between those living close to major roads and those living further away to identify a causal effect. The results show that the phase-out led to a large reduction in infant mortality, particularly among girls. This effect was driven by infants born to mothers with low socioeconomic status.The third study investigates how exposure to lead pollution in early life affects cognitive skills among school age children in Uganda. Again, it relies on the phase-out of leaded gasoline as an exogenous shock to lead pollution levels. The findings suggest a strong negative effect of lead pollution on math and English test scores, which is stronger for children exposed to lead pollution at an earlier age.Taken together, these studies contribute to our understanding of the benefits of more stringent environmental regulations regarding heavy metal pollution. (Less)
A structural insight into mechanical strength of graphene-like carbon and carbon nitride networks

Graphene, one of the strongest materials ever discovered, triggered the exploration of many 2D materials in the last decade. However, the successful synthesis of a stable nanomaterial requires a rudimentary understanding of the relationship between its structure and strength. In the present study, we investigate the mechanical properties of eight different carbon-based 2D nanomaterials by performing extensive density functional theory calculations. The considered structures were just recently either experimentally synthesized or theoretically predicted. The corresponding stress–strain curves and elastic moduli are reported. They can be useful in training force field parameters for large scale simulations. A comparative analysis of these results revealed a direct relationship between atomic density per area and elastic modulus. Furthermore, for the networks that have an armchair and a zigzag orientation, we observed that they were more stretchable in the zigzag direction than the armchair direction. A critical analysis of the angular distributions and radial distribution functions suggested that it could be due to the higher ability of the networks to suppress the elongations of the bonds in the zigzag direction by deforming the bond angles. The structural interpretations provided in this work not only improve the general understanding of a 2D material’s strength but also enables us to rationally design them for higher qualities.
Convergence of Proximal-Gradient Stochastic Variational Inference under Non-Decreasing Step-Size Sequence

Stochastic approximation methods have recently gained popularity for variational inference, but many existing approaches treat them as "black-box" tools. Thus, they often do not take advantage of the geometry of the posterior and usually require a decreasing sequence of step-sizes (which converges slowly in practice). We introduce a new stochastic-approximation method that uses a proximal-gradient framework. Our method exploits the geometry and structure of the variational lower bound, and contains many existing methods, such as stochastic variational inference, as a special case. We establish the convergence of our method under a "non-decreasing" step-size schedule, which has both theoretical and practical advantages. We consider setting the step-size based on the continuity of the objective and the geometry of the posterior, and show that our method gives a faster rate of convergence for variational-Gaussian inference than existing stochastic methods.
Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision (DD) fusion method, the performance optimization of individual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.
Relationship Between Circadian Blood Pressure Patterns and Progression of Early Carotid Atherosclerosis: A 3-Year Follow-Up Study

BackgroundArterial hypertension is a major risk factor for cardiovascular damage. The results of several studies suggest that target organ damage is greater in hypertensive persons with high blood pressure variability. Methods and ResultsDuring 3.3 years of follow-up, we studied the relationship between circadian blood pressure changes and the progression of early carotid atherosclerosis in 286 patients aged >55 years. Blood pressure patterns were evaluated with a long-term blood pressure monitor, and the extent of atherosclerosis was measured as the intima-media wall thickness (IMT) of the common carotid artery. Patients were subdivided according to blood pressure variability. The progression of IMT was significantly greater in the patients with increased systolic blood pressure variability (0.11 mm/y [95% CI 0.09 to 0.14] versus 0.05 mm/y [0.03 to 0.08];P <0.005) even after adjustment for other risk factors. Multivariate regression analysis revealed the daytime systolic blood pressure variability to be the best predictor for the progression of IMT. Raised daytime systolic blood pressure variability (>15 mm Hg) is associated with an increased relative risk of the development of early atherosclerosis (3.9 [1.4 to 11.1];P <0.01) and of cardiovascular events (1.87 [1.08 to 3.20];P <0.01). ConclusionsThe daytime systolic blood pressure variability is a strong predictor of early carotid atherosclerosis progression and is useful to define the risk-benefit ratio of therapeutic approaches.
Anchoring of Surface Proteins to the Cell Wall of Staphylococcus aureus

Surface proteins of Staphylococcus aureus are anchored to the cell wall peptidoglycan by a mechanism requiring a C-terminal sorting signal with a LPXTG motif. Sortase cleaves polypeptides between the threonine and the glycine of the LPXTG motif. The carboxyl group of threonine is subsequently amide-linked to the amino group of peptidoglycan cross-bridges. The three-dimensional structure of sortase revealed the close proximity of the catalytic site residue cysteine 184 with histidine 120; however, no structural evidence for a thiolate-imidazolium ion pair could be detected. We report that alanine substitution of either cysteine 184 or histidine 120 abolishes in vivo and in vitro sorting reactions. Further, alanine substitution of tryptophan 194, a residue that is in close proximity of histidine 120, reduces the transpeptidase activity of sortase. These results suggest a model whereby sortase forms a thiolate-imidazolium ion pair for the catalysis of its transpeptidation reaction and that the position of tryptophan 194 assists in the formation of this ion pair.
Preventing preterm birth: the past limitations and new potential of animal models

The high rate of preterm birth in the USA and many other countries is a potential target for improving children’s immediate health and reducing the medical problems they face as adults. The acute complications for infants born prematurely often require intensive care management and are followed by long-lasting cognitive, sensory, motor, and cardiovascular deficits that substantially limit adult capabilities and survival. The inability to effectively reduce preterm birth stems from the failure to understand normal mechanisms of parturition in humans. Although studies from several model organisms help define the physiology of maintenance and termination of pregnancy, there are fundamental differences between species. For example, species regulate their production of progesterone, the crucial hormone in sustaining pregnancy, differently. This limits the extent to which models can provide meaningful information about the physiological mechanisms of human gestation. The growing wealth of sequenced mammalian genomes, computational comparative genomic tools and systems biology approaches provides new potential to utilize the divergence of DNA sequences and physiology between species to understand the genetic underpinnings of preterm birth.
Diabetic autonomic neuropathy in children: immediate heart‐rate response to standing

ABSTRACT. The immediate heart‐rate response to standing was used to investigate possible autonomic neuropathy in a group of 38 insulin‐dependent diabetic patients in the paediatric age group. The controls and most of the diabetics showed the characteristic response to standing of a rapid increase in heart‐rate and a fall to the resting rate within 15 seconds. Some diabetics showed a flat response or a prolonged gradual increase of heart‐rate on standing. The usual method of describing the change in heart rate that occurs in response to standing is to compare the R‐R intervals at the 30th and 15th beats (30:15 ratio). This is considered less appropriate in children because of the wider variability in heart rate due to sinus arrhythmia. An alternative ratio, the “maximum R‐R/minimum R‐R ratio'’is proposed. This ratio is calculated by dividing the length of the maximum R‐R interval (which occurred after the minimum R‐R interval during the 30 second recording) by the length of the minimum R‐R interval. Compared to 38 index‐selected age and sex matched controls, the diabetics showed a significantly lower mean “maximum R‐R/minimum R‐R ratio (P = 0.033). Six of the diabetics had results lower than the lowest control result. This test gives a prevalence rate of changes suggestive of diabetic autonomic neuropathy of approximately 15% in this age group.
Topological Landscapes: A Terrain Metaphor for Scientific Data

Scientific visualization and illustration tools are designed to help people understand the structure and complexity of scientific data with images that are as informative and intuitive as possible. In this context the use of metaphors plays an important role since they make complex information easily accessible by using commonly known concepts. In this paper we propose a new metaphor, called "topological landscapes," which facilitates understanding the topological structure of scalar functions. The basic idea is to construct a terrain with the same topology as a given dataset and to display the terrain as an easily understood representation of the actual input data. In this projection from an n-dimensional scalar function to a two-dimensional (2D) model we preserve function values of critical points, the persistence (function span) of topological features, and one possible additional metric property (in our examples volume). By displaying this topologically equivalent landscape together with the original data we harness the natural human proficiency in understanding terrain topography and make complex topological information easily accessible.
Predicting Class I Major Histocompatibility Complex (MHC) Binders Using Multivariate Statistics: Comparison of Discriminant Analysis and Multiple Linear Regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.
Antiretroviral Drugs for Tuberculosis Control in the Era of HIV/AIDS

Human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) has dramatically increased the incidence of tuberculosis (TB) in subSaharan Africa, where up to 60% of TB patients are coinfected with HIV and each year 200,000 TB deaths are attributable to HIV coinfection. Now HIV threatens control of TB in Asia, Eastern Europe, and Latin America. Antiretroviral (ARV) drugs can prevent TB by preserving immunity, but cohort analysis shows that early therapy, plus high levels of coverage and compliance, will be needed to avert a significant fraction of TB cases. However, ARV drugs could enhance the treatment of TB, and TB programs provide an important entry point for the treatment of HIV/AIDS.
A co-simulation study of adaptive EPIC computing

Reconfigurable computing offers the embedded systems designers the flexibility of application specific optimizations on a generic platform. In this paper, we are concerned with a fine-grain, tightly coupled, dynamically reconfigurable architecture we call Adaptive EPIC. A generic EPIC architecture is augmented with a dynamically reconfigurable structure. In this paper, we describe an experimental setup to evaluate the performance of such a processor. Our results show that such architecture can offer significant performance improvements for low frequency, and hence low power, core processors.
Strategies to Improve and Evaluate Physics‐Based Hyperresolution Hydrologic Simulations at Regional Basin Scales

The application of physics‐based distributed hydrologic models (DHMs) at hyperresolutions (~100 m) is expected to support several water‐related applications but is still prevented by critical data, model validation, and computational challenges. In this study, we address some of these challenges by applying the TIN‐based Real‐time Integrated Basin Simulator DHM at a nominal resolution of ~88 m in the Río Sonora basin, a regional watershed of ~21,000 km2 in northwest Mexico. First, we generate reliable high‐resolution (1‐km) hydrometeorological forcings by bias correcting reanalysis products with ground observations and applying downscaling routines that use terrain information at high resolution, which is available globally. Second, we develop a strategy to obtain high‐resolution (250‐m) grids of soil parameters by integrating a coarse‐resolution soil map based on the Food and Agriculture Organization classification with recently released high‐resolution global data sets. Third, we apply the model over a decadal period (2004–2013) and use a set of complementary tools, including Taylor diagrams, connectivity analysis, and empirical orthogonal function analysis, to assess its ability to simulate spatial patterns of land surface temperature through comparison with daily remotely sensed products. We find that (i) the hyperresolution‐simulated patterns capture the spatial variability of land surface temperature quite well and (ii) vegetation properties are the major physical factors controlling the discrepancies between simulated and remotely sensed products. The strategies presented here are based on global data sets and robust statistical techniques that can be utilized in different settings with other DHMs, and thus, they provide valuable support for the scientific community focused on hyperresolution hydrologic modeling.
Low negative predictive value of skin tests in investigating delayed reactions to radio‐contrast media

Delayed reactions to radio‐contrast media (RCM) with positive skin tests are rare. We report the study of a series of 15 patients who presented delayed reactions to RCM, with an analysis of the clinical features and the results of standardized drug skin tests. Patch tests were performed with RCM and iodized antiseptics (IAs). If negative, prick tests were performed, followed by intradermal tests (IDTs), then intravenous administration under hospital surveillance. The main clinical features were maculopapular rashes or a macular rubella‐like rashes. Patch tests were positive with RCM in 2 of 15 cases and with IAs in 4 of 15 cases. All the prick tests were negative. IDTs were positive at 24 h in 8 of 15 cases. 5 of 12 patients had a non‐severe relapse of the rash upon receiving an RCM despite clearly negative skin tests with the readministered RCM. Visipaque® cross‐reacted with Iopamiron®, Iomeron®, Telebrix®, Omnipaque®, Xenetix® and Hexabrix®. Omnipaque® cross‐reacted with Hexabrix® and Iopamiron®. IDTs with delayed readings are of better value than patch tests in such patients. The readministration of RCM with negative IDTs must be performed with progressive amounts under hospital surveillance. Cross‐reactions between various classes of RCM are frequent. The responsible epitopes are unknown. Iodine itself could be involved.
Thiazolidinediones and Risk of Long-Term Dialysis in Diabetic Patients with Advanced Chronic Kidney Disease: A Nationwide Cohort Study

Thiazolidinediones (TZDs) reduce urinary albumin excretion and proteinuria in diabetic nephropathy. The effect of TZDs on hard renal outcome in diabetic patients with chronic kidney disease (CKD) is unknown. We investigate the association of TZDs and risk of long-term dialysis or death in diabetic patients with advanced CKD. The nationwide population-based cohort study was conducted using Taiwan’s National Health Insurance Research Database. From January 2000 to June 2009, 12350 diabetic patients with advanced CKD (serum creatinine levels greater than 6 mg/dL but not yet receiving renal replacement therapy) were selected for the study. We used multivariable Cox regression models and a propensity score-based matching technique to estimate hazard ratios (HRs) for development of long-term dialysis and the composite outcome of long-term dialysis or death for TZD users (n=1224) as compared to nonusers (n=11126). During a median follow-up of 6 months, 8270 (67.0%) patients required long-term dialysis and 2593 (21.0%) patients died before starting long-term dialysis. Using propensity score matched analysis, we found TZD users were associated with a lower risk for long-term dialysis (HR, 0.80; 95% confidence interval [CI], 0.74-0.86) and the composite outcome of long-term dialysis or death (HR, 0.85; 95% CI, 0.80-0.91). The results were consistent across most patient subgroups. Use of TZDs among diabetic patients with advanced CKD was associated with lower risk for progression to end-stage renal disease necessitating long-term dialysis or death. Further randomized controlled studies are required to validate this association.