Why we should use topological data analysis in ageing: Towards defining the "topological shape of ageing".

Living systems are subject to the arrow of time; from birth, they undergo complex transformations (self-organization) in a constant battle for survival, but inevitably ageing and disease trap them to death. Can ageing be understood and eventually reversed? What tools can be employed to further our understanding of ageing? The present article is an invitation for biologists and clinicians to consider key conceptual ideas and computational tools (known to mathematicians and physicists), which potentially may help dissect some of the underlying processes of ageing and disease. Specifically, we first discuss how to classify and analyse complex systems, as well as highlight critical theoretical difficulties that make complex systems hard to study. Subsequently, we introduce Topological Data Analysis - a novel Big Data tool - which may help in the study of complex systems since it extracts knowledge from data in a holistic approach via topological considerations. These conceptual ideas and tools are discussed in a relatively informal way to pave future discussions and collaborations between mathematicians and biologists studying ageing.

Dereplication of Flavonoid Glycoconjugates from Adenocalymma imperatoris-maximilianii by Untargeted Tandem Mass Spectrometry-Based Molecular Networking.

The interpretation of large datasets acquired using high performance liquid chromatography coupled with tandem mass spectrometry represents one of the major challenges in natural products research. Here we propose the use of molecular networking to rapid identify the known secondary metabolites from untargeted MS/MS analysis of Adenocalymma imperatoris-maximilianii plant extracts. The leaves, stems and roots of A. imperatoris-maximilianii were extracted using different solvents according to Snyder selectivity triangle. The samples were analyzed by HPLC coupled with ion trap mass spectrometer in a collision-induced dissociation MS/MS configuration in both positive and negative electrospray ionization modes. Molecular networking simultaneously organized the spectra by cosine similarity. The chemical identification was performed based on the systematic study of the main fragmentation pathways observed for the resulting network. The untargeted tandem mass spectrometry-based molecular networking allowed for the identification of 63 metabolites, mainly mono-, di- and tri-, C- and/or O-glycosyl flavones. Molecular networking was capable not only to dereplicate known flavonoids, but also to point out related prenyl derivatives, described for the first time in Adenocalymma species. The gas-phase reaction route to form the characteristic [M-H2O-(30/60/90)]+ fragments in C-glycosyl flavones was suggested as sequential sugar ring opening followed by retro-aldol elimination involving aldose-ketose isomerization. The use of molecular networking with LC-CID-MS/MS assisted the identification of various isomeric and isobaric flavonoid glycoconjugates by establishing clusters according to the fragmentation similarities. Additionally, the proposed cross-ring sugar cleavages can contribute to the identification of C-glycosides by MS/MS analysis.

Context representation and fusion: advancements and opportunities.

The acceptance and usability of context-aware systems have given them the edge of wide use in various domains and has also attracted the attention of researchers in the area of context-aware computing. Making user context information available to such systems is the center of attention. However, there is very little emphasis given to the process of context representation and context fusion which are integral parts of context-aware systems. Context representation and fusion facilitate in recognizing the dependency/relationship of one data source on another to extract a better understanding of user context. The problem is more critical when data is emerging from heterogeneous sources of diverse nature like sensors, user profiles, and social interactions and also at different timestamps. Both the processes of context representation and fusion are followed in one way or another; however, they are not discussed explicitly for the realization of context-aware systems. In other words most of the context-aware systems underestimate the importance context representation and fusion. This research has explicitly focused on the importance of both the processes of context representation and fusion and has streamlined their existence in the overall architecture of context-aware systems' design and development. Various applications of context representation and fusion in context-aware systems are also highlighted in this research. A detailed review on both the processes is provided in this research with their applications. Future research directions (challenges) are also highlighted which needs proper attention for the purpose of achieving the goal of realizing context-aware systems.

Application of random forests to select premium quality vegetable oils by their fatty acid composition.

In order to discriminate premium quality from inexpensive edible oils, the fatty acid profiles of tea, rapeseed, corn, sunflower and sesame oil were compared with the ones from extra virgin olive oil (EVOO). Fatty acid methyl esters were quantified by GC/MS. Principal component analysis (PCA) and random forests (RF) were applied to cluster the samples. RF showed a better ability of discrimination and also revealed the contribution of each variable to the clustering model. The multidimensional scaling (MDS) plot of the RF proximity matrix demonstrated that tea oil was similar to EVOO. Meanwhile, it was observed that the total content of cis-monounsaturated fatty acids (79.48%) in tea oil was close to EVOO (80.71%), especially the oleic acid (77.38% and 77.45%, respectively). The results suggest that tea oil might be a good edible oil choice, considering the high oleic acid content and similar fatty acid profiles compared to those of EVOO.

VinaMPI: facilitating multiple receptor high-throughput virtual docking on high-performance computers.

The program VinaMPI has been developed to enable massively large virtual drug screens on leadership-class computing resources, using a large number of cores to decrease the time-to-completion of the screen. VinaMPI is a massively parallel Message Passing Interface (MPI) program based on the multithreaded virtual docking program AutodockVina, and is used to distribute tasks while multithreading is used to speed-up individual docking tasks. VinaMPI uses a distribution scheme in which tasks are evenly distributed to the workers based on the complexity of each task, as defined by the number of rotatable bonds in each chemical compound investigated. VinaMPI efficiently handles multiple proteins in a ligand screen, allowing for high-throughput inverse docking that presents new opportunities for improving the efficiency of the drug discovery pipeline. VinaMPI successfully ran on 84,672 cores with a continual decrease in job completion time with increasing core count. The ratio of the number of tasks in a screening to the number of workers should be at least around 100 in order to have a good load balance and an optimal job completion time. The code is freely available and downloadable. Instructions for downloading and using the code are provided in the Supporting Information.

[Mobile phone based data acquisition and evaluation system for the alternative four diagnostic methods of traditional Chinese medicine].

This study is dedicated to integrate the theories of the four diagnostic methods of TCM and the methods of mobile healthcare so as to achieve the goal of the four diagnostic functions of TCM on mobile phone. An Android smartphone based data acquisition system has been developed and experimentally demonstrated. It was shown that the prototype could successfully achieve the fundamental function of the four diagnostic methods of TCM and thus help preliminarily interpret the symptoms of human diseases.

Sensory evaluation of the taste of berberine hydrochloride using an Electronic Tongue.

BACKGROUND: The "Electronic Tongue" is an instrument that can be trained to screen the taste attributes of formulations within a rapid timeframe when used in conjunction with sensory panel taste assessment data. PURPOSE: The purpose of this research was to demonstrate that a sensory instrument for taste (e-Tongue) could be used to evaluate the bitterness of berberine hydrochloride from Chinese medicinal herbs. METHODS: Several flavorful native compounds were tested by the e-Tongue. Data from a human sensory panel was collected to train the e-Tongue. The e-Tongue was then used to establish the correlation between data from the sensory panel, and to predict the bitterness scores of berberine hydrochloride. RESULTS: The e-Tongue showed different response patterns for different tastes or strengths of flavor compounds. No significant differences were found between the results of the e-Tongue and the sensory taste panel. CONCLUSIONS: The e-Tongue could be used to evaluate the effect of bitterness of berberine hydrochloride. Therefore, e-Tongues showed potential to replace sensory panel evaluations in future experiments regarding Chinese traditional medicine.

Demographic and clinical characteristics of middle-aged versus younger adults enrolled in a clinical trial of a web-delivered psychosocial treatment for substance use disorders.

OBJECTIVE: Evidence suggests that substance abuse is becoming more prevalent in middle-aged adults. The objective of this secondary analysis was to add to the growing empirical literature on the unique features of middle-aged substance abuse populations. METHODS: We descriptively compared baseline demographic and clinical characteristics of middle-aged (age 45-62 years, n = 111) and younger (age 18-44 years, n = 395) substance abusers entering a Web-based psychosocial treatment study as part of the National Institute on Drug Abuse Clinical Trials Network. RESULTS: A significantly greater percentage of middle-aged adults were nonwhite and had a marital status other than single/never married. There was a significant association between frequency of Internet use and the age group. Forty-six percent of middle-aged adults versus 21% of younger adults reported no Internet use in the prior 90 days. A significantly greater percentage of middle-aged adults used cocaine, and a significantly greater percentage of younger adults used marijuana and opioids. Clinically significant cognitive impairment (z < -1.0) was found for the average participant in both groups on logical association of familiar concepts. CONCLUSIONS: This secondary analysis of a National Institute on Drug Abuse Clinical Trials Network study provides additional information on the unique features of middle-aged substance abusers. Increasing knowledge of similarities and differences between younger and middle-aged substance abusers can help with potential age-specific substance abuse treatment planning.

Mobile phone based data acquisition and evaluation system for the alternative four diagnostic methods of traditional Chinese medicine / 中国医疗器械杂志

This study is dedicated to integrate the theories of the four diagnostic methods of TCM and the methods of mobile healthcare so as to achieve the goal of the four diagnostic functions of TCM on mobile phone. An Android smartphone based data acquisition system has been developed and experimentally demonstrated. It was shown that the prototype could successfully achieve the fundamental function of the four diagnostic methods of TCM and thus help preliminarily interpret the symptoms of human diseases.

Traditional healers formalised?

Traditional healers are the first to be called for help when illness strikes the majority of South Africans. Their communities have faith in their ability to cure or alleviate conditions managed by doctors, and much more. A visit to such practitioners' websites (they are up with the latest advertising technology!) shows that they promise help with providing more power, love, security or money, protection from evil people and spirits, enhancing one's sex life with penis enlargement and vagina tightening spells, etc. Contemplating such claims, it is easy to be dismissive of traditional healers. But in this issue of the SAMJ Nompumelelo Mbatha and colleagues1 argue that the traditional healers' regulatory council, promised by an Act of Parliament, should be established, followed by (or preferably preceded by) formal recognition by employers of sick certificates issued by traditional healers. Can matters be so simply resolved? What does this mean for doctors and other formally recognised healthcare professionals, and how to respond to such claims and social pressures?

Stochastic simulation of uranium migration at the Hanford 300 Area.

This work focuses on the quantification of groundwater flow and subsequent U(VI) transport uncertainty due to heterogeneity in the sediment permeability at the Hanford 300 Area. U(VI) migration at the site is simulated with multiple realizations of stochastically-generated high resolution permeability fields and comparisons are made of cumulative water and U(VI) flux to the Columbia River. The massively parallel reactive flow and transport code PFLOTRAN is employed utilizing 40,960 processor cores on DOE's petascale Jaguar supercomputer to simultaneously execute 10 transient, variably-saturated groundwater flow and U(VI) transport simulations within 3D heterogeneous permeability fields using the code's multi-realization simulation capability. Simulation results demonstrate that the cumulative U(VI) flux to the Columbia River is less responsive to fine scale heterogeneity in permeability and more sensitive to the distribution of permeability within the river hyporheic zone and mean permeability of larger-scale geologic structures at the site.

Computing moment-to-moment BOLD activation for real-time neurofeedback.

Estimating moment-to-moment changes in blood oxygenation level dependent (BOLD) activation levels from functional magnetic resonance imaging (fMRI) data has applications for learned regulation of regional activation, brain state monitoring, and brain-machine interfaces. In each of these contexts, accurate estimation of the BOLD signal in as little time as possible is desired. This is a challenging problem due to the low signal-to-noise ratio of fMRI data. Previous methods for real-time fMRI analysis have either sacrificed the ability to compute moment-to-moment activation changes by averaging several acquisitions into a single activation estimate or have sacrificed accuracy by failing to account for prominent sources of noise in the fMRI signal. Here we present a new method for computing the amount of activation present in a single fMRI acquisition that separates moment-to-moment changes in the fMRI signal intensity attributable to neural sources from those due to noise, resulting in a feedback signal more reflective of neural activation. This method computes an incremental general linear model fit to the fMRI time series, which is used to calculate the expected signal intensity at each new acquisition. The difference between the measured intensity and the expected intensity is scaled by the variance of the estimator in order to transform this residual difference into a statistic. Both synthetic and real data were used to validate this method and compare it to the only other published real-time fMRI method.

[Feature selection based on correlation degree and its application in traditional Chinese medicine].

Mutual information can measure arbitrary statistical dependencies. It has been applied to many kinds of fields widely. But when mutual information is used as the correlation measure, the features with more values are apt to be chosen. To solve this problem, a novel definition of correlation degree is proposed in this paper. It can avoid the shortcoming of selecting more value features when mutual information acted as the measure, and it can avoid the shortcoming of selecting less value features when correlation degree coefficients acted as the measure. In the method using the novel definition, the number of selected features is determined by the correct classification rate of Support Vector Machine. At last, the efficiency of the method is illustrated through analyzing the symptoms combination of seven essential elements of the syndrome corresponding to stroke.

Feature selection based on correlation degree and its application in traditional Chinese medicine / 生物医学工程学杂志

Mutual information can measure arbitrary statistical dependencies. It has been applied to many kinds of fields widely. But when mutual information is used as the correlation measure, the features with more values are apt to be chosen. To solve this problem, a novel definition of correlation degree is proposed in this paper. It can avoid the shortcoming of selecting more value features when mutual information acted as the measure, and it can avoid the shortcoming of selecting less value features when correlation degree coefficients acted as the measure. In the method using the novel definition, the number of selected features is determined by the correct classification rate of Support Vector Machine. At last, the efficiency of the method is illustrated through analyzing the symptoms combination of seven essential elements of the syndrome corresponding to stroke.

[Design of a miniaturized blood temperature-varying system based on computer distributed control].

Blood temperature-varying has been widely applied in clinical practice such as extracorporeal circulation for whole-body perfusion hyperthermia (WBPH), body rewarming and blood temperature-varying in organ transplantation. This paper reports a novel DCS (Computer distributed control)-based blood temperature-varying system which includes therapy management function and whose hardware and software can be extended easily. Simulation results illustrate that this system provides precise temperature control with good performance in various operation conditions.

Design of a miniaturized blood temperature-varying system based on computer distributed control / 生物医学工程学杂志

Blood temperature-varying has been widely applied in clinical practice such as extracorporeal circulation for whole-body perfusion hyperthermia (WBPH), body rewarming and blood temperature-varying in organ transplantation. This paper reports a novel DCS (Computer distributed control)-based blood temperature-varying system which includes therapy management function and whose hardware and software can be extended easily. Simulation results illustrate that this system provides precise temperature control with good performance in various operation conditions.

Analysis of data fusion methods in virtual screening: similarity and group fusion.

In a recent companion paper we have related the operation of simple data fusion rules used in virtual screening to a multiple integral formalism. In this paper we extend these ideas to the analysis of data fusion methods applied to real data. We examine several cases of similarity fusion using different coefficients and different representations and consider the reasons for positive or negative results in terms of the similarity distributions. Results are obtained using the SUM-, MAX- MIN-, and CombMNZ-fusion rules. We also develop a customized fusion rule, which provides an estimate of the optimal possible result for fusing multiple searches of a specific database; this shows that similarity fusion can, in principle, achieve retrieval enhancements even if this is not achieved in practice with current fusion rules. The methods are extended to analyze the comparatively successful results of group fusion with multiple actives, and we provide a rationale for the observed superiority of the MAX-rule over the SUM-rule in this context.

Design and evaluation of a novel class-directed 2D fingerprint to search for structurally diverse active compounds.

Recent attempts to increase similarity search performance using molecular fingerprints have mostly focused on the evaluation of alternative similarity metrics or scoring schemes, rather than the development of new types of fingerprints. Here, we introduce a novel 2D fingerprint design (property descriptor value range-derived fingerprint or PDR-FP) that involves activity-oriented selection of property descriptors and the transformation of descriptor value ranges into a binary format such that each fingerprint bit position represents a specific value interval. The design is tailored toward multiple-template similarity searching and permits training on specific activity classes. In search calculations on 15 compound classes of increasing structural diversity, the PDR fingerprint performed better than other state-of-the-art 2D fingerprints. Among the structurally diverse classes were six compound sets with peptide character, which represent a notoriously difficult chemotype for 2D similarity searching. In these cases, PDR-FP produced promising results, whereas other fingerprint methods mostly failed. PDR-FP is specifically designed for search calculations on structurally diverse compounds, and these calculations are not influenced by molecular size effects, which represent a general problem for similarity searching using bit string representations.

Predicting protein structural class with pseudo-amino acid composition and support vector machine fusion network.

Because a priori knowledge of a protein structural class can provide useful information about its overall structure, the determination of protein structural class is a quite meaningful topic in protein science. However, with the rapid increase in newly found protein sequences entering into databanks, it is both time-consuming and expensive to do so based solely on experimental techniques. Therefore, it is vitally important to develop a computational method for predicting the protein structural class quickly and accurately. To deal with the challenge, this article presents a dual-layer support vector machine (SVM) fusion network that is featured by using a different pseudo-amino acid composition (PseAA). The PseAA here contains much information that is related to the sequence order of a protein and the distribution of the hydrophobic amino acids along its chain. As a showcase, the rigorous jackknife cross-validation test was performed on the two benchmark data sets constructed by Zhou. A significant enhancement in success rates was observed, indicating that the current approach may serve as a powerful complementary tool to other existing methods in this area.

Analysing the output from primary screening.

From a perspective of process knowledge and enhancement, the analysis of the results of biological screening should not be limited to the outcome of specific projects, but additionally encompass a process centric view. Summarising outcomes across multiple projects is a powerful tool to gain a greater understanding of biological screening that will also enable optimisation of the strategy for specific projects or target classes. We have analysed a set of 73,651 compounds with reproducible (confirmed) results from 63 high-throughput screening (HTS) campaigns to reveal the underlying trends in the population of active compounds. We have focused on the overall physico-chemical profile of compound populations derived from biological screening since the in vivo activity of drug molecules is the result of physico-chemical and structural properties of the compound.