Verifying the fully “Laplacianised” posterior Naïve Bayesian approach and more

Mussa and Glen would like to thank Unilever for financial support, whereas Mussa and Mitchell thank the BBSRC for funding this research through grant BB/I00596X/1. Mitchell thanks the Scottish Universities Life Sciences Alliance (SULSA) for financial support.Background In a recent paper, Mussa, Mitchell and Glen (MMG) have mathematically demonstrated that the “Laplacian Corrected Modified Naïve Bayes” (LCMNB) algorithm can be viewed as a variant of the so-called Standard Naïve Bayes (SNB) scheme, whereby the role played by absence of compound features in classifying/assigning the compound to its appropriate class is ignored. MMG have also proffered guidelines regarding the conditions under which this omission may hold. Utilising three data sets, the present paper examines the validity of these guidelines in practice. The paper also extends MMG’s work and introduces a new version of the SNB classifier: “Tapered Naïve Bayes” (TNB). TNB does not discard the role of absence of a feature out of hand, nor does it fully consider its role. Hence, TNB encapsulates both SNB and LCMNB. Results LCMNB, SNB and TNB performed differently on classifying 4,658, 5,031 and 1,149 ligands (all chosen from the ChEMBL Database) distributed over 31 enzymes, 23 membrane receptors, and one ion-channel, four transporters and one transcription factor as their target proteins. When the number of features utilised was equal to or smaller than the “optimal” number of features for a given data set, SNB classifiers systematically gave better classification results than those yielded by LCMNB classifiers. The opposite was true when the number of features employed was markedly larger than the “optimal” number of features for this data set. Nonetheless, these LCMNB performances were worse than the classification performance achieved by SNB when the “optimal” number of features for the data set was utilised. TNB classifiers systematically outperformed both SNB and LCMNB classifiers. Conclusions The classification results obtained in this study concur with the mathematical based guidelines given in MMG’s paper—that is, ignoring the role of absence of a feature out of hand does not necessarily improve classification performance of the SNB approach; if anything, it could make the performance of the SNB method worse. The results obtained also lend support to the rationale, on which the TNB algorithm rests: handled judiciously, taking into account absence of features can enhance (not impair) the discriminatory classification power of the SNB approach.Publisher PDFPeer reviewe

Социально-философский анализ процессов модернизации в Китайской Народной Республике

Проанализированы основные изменения, произошедшие в обществе, в политической системе Китая в связи с началом реформ и модернизации после прихода к власти Дэн Сяопина. Дан анализ основных положений программы модернизации, предложенной руководством КНР. Освещены теоретико-методологические предпосылки модернизации КНР. Выделены основные мировоззренческие и методологические элементы теории социализма с китайской специфики

Post-Operative Medium- and Long-Term Endocrine Outcomes in Patients with Non-Functioning Pituitary Adenomas—Machine Learning Analysis

Post-operative endocrine outcomes in patients with non-functioning pituitary adenoma (NFPA) are variable. The aim of this study was to use machine learning (ML) models to better predict medium- and long-term post-operative hypopituitarism in patients with NFPAs. We included data from 383 patients who underwent surgery with or without radiotherapy for NFPAs, with a follow-up period between 6 months and 15 years. ML models, including k-nearest neighbour (KNN), support vector machine (SVM), and decision tree models, showed a superior ability to predict panhypopituitarism compared with non-parametric statistical modelling (mean accuracy: 0.89; mean AUC-ROC: 0.79), with SVM achieving the highest performance (mean accuracy: 0.94; mean AUC-ROC: 0.88). Pre-operative endocrine function was the strongest feature for predicting panhypopituitarism within 1 year post-operatively, while endocrine outcomes at 1 year post-operatively supported strong predictions of panhypopituitarism at 5 and 10 years post-operatively. Other features found to contribute to panhypopituitarism prediction were age, volume of tumour, and the use of radiotherapy. In conclusion, our study demonstrates that ML models show potential in predicting post-operative panhypopituitarism in the medium and long term in patients with NFPM. Future work will include incorporating additional, more granular data, including imaging and operative video data, across multiple centres

Differential Gene Expression to Investigate the Effects of Low-level Electrochemical Currents on Bacillus subtilis

With the emergence and spread of multidrug resistant bacteria, effective methods to eliminate both planktonic bacteria and those embedded in surface-attached biofilms are needed. Electric currents at μA-mA/cm2 range are known to reduce the viability of bacteria. However, the mechanism of such effects is still not well understood. In this study, Bacillus subtilis was used as the model Gram-positive species to systematically investigate the effects of electrochemical currents on bacteria including the morphology, viability, and gene expression of planktonic cells, and viability of biofilm cells. The data suggest that weak electrochemical currents can effectively eliminate B. subtilis both as planktonic cells and in biofilms. DNA microarray results indicate that the genes associated with oxidative stress response, nutrient starvation, and membrane functions were induced by electrochemical currents. These findings suggest that ions and oxidative species generated by electrochemical reactions might be important for the killing effects of these currents

Gulf-Wide Decreases in the Size of Large Coastal Sharks Documented by Generations of Fishermen

Large sharks are top predators in most coastal and marine ecosystems throughout the world, and evidence of their reduced prominence in marine ecosystems has been a serious concern for fisheries and ecosystem management. Unfortunately, quantitative data to document the extent, timing, and consequences of changes in shark populations are scarce, thwarting examination of long-term (decadal, century) trends, and reconstructions based on incomplete data sets have been the subject of debate. Absence of quantitative descriptors of past ecological conditions is a generic problem facing many fields of science but is particularly troublesome for fisheries scientists who must develop specific targets for restoration. We were able to use quantitative measurements of shark sizes collected annually and independently of any scientific survey by thousands of recreational fishermen over the last century to document decreases in the size of large sharks from the northern Gulf of Mexico. Based on records from fishing rodeos in three U.S. coastal states, the size (weight or length) of large sharks captured by fishermen decreased by 50–70% during the 20 years after the 1980s. The pattern is largely driven by reductions in the occurrence and sizes of Tiger Sharks Galeocerdo cuvier and Bull Sharks Carcharhinus leucas and to a lesser extent Hammerheads Sphyrna spp. This decrease occurred despite increasing fishing effort and advances in technology, but it is coincident with the capitalization of the U.S. commercial shark long-line fishery in the GOM

Relaxation equations for two-dimensional turbulent flows with a prior vorticity distribution

Using a Maximum Entropy Production Principle (MEPP), we derive a new type of relaxation equations for two-dimensional turbulent flows in the case where a prior vorticity distribution is prescribed instead of the Casimir constraints [Ellis, Haven, Turkington, Nonlin., 15, 239 (2002)]. The particular case of a Gaussian prior is specifically treated in connection to minimum enstrophy states and Fofonoff flows. These relaxation equations are compared with other relaxation equations proposed by Robert and Sommeria [Phys. Rev. Lett. 69, 2776 (1992)] and Chavanis [Physica D, 237, 1998 (2008)]. They can provide a small-scale parametrization of 2D turbulence or serve as numerical algorithms to compute maximum entropy states with appropriate constraints. We perform numerical simulations of these relaxation equations in order to illustrate geometry induced phase transitions in geophysical flows.Comment: 21 pages, 9 figure

Environment-Sensitive Epigenetics and the Heritability of Complex Diseases

Genome-wide association studies have thus far failed to explain the observed heritability of complex human diseases. This is referred to as the “missing heritability” problem. However, these analyses have usually neglected to consider a role for epigenetic variation, which has been associated with many human diseases. We extend models of epigenetic inheritance to investigate whether environment-sensitive epigenetic modifications of DNA might explain observed patterns of familial aggregation. We find that variation in epigenetic state and environmental state can result in highly heritable phenotypes through a combination of epigenetic and environmental inheritance. These two inheritance processes together can produce familial covariances significantly higher than those predicted by models of purely epigenetic inheritance and similar to those expected from genetic effects. The results suggest that epigenetic variation, inherited both directly and through shared environmental effects, may make a key contribution to the missing heritability