Functional brain connectivity and cognition: effects of adult age and task demands

Previous neuroimaging research has documented that patterns of intrinsic (resting state) functional connectivity (FC) among brain regions covary with individual measures of cognitive performance. Here, we examined the relation between intrinsic FC and a reaction time (RT) measure of performance, as a function of age group and task demands. We obtained filtered, event-related functional magnetic resonance imaging data, and RT measures of visual search performance, from 21 younger adults (19–29 years old) and 21 healthy, older adults (60–87 years old). Age-related decline occurred in the connectivity strength in multiple brain regions, consistent with previous findings. Among 8 pairs of regions, across somatomotor, orbitofrontal, and subcortical networks, increasing FC was associated with faster responding (lower RT). Relative to younger adults, older adults exhibited a lower strength of this RT-connectivity relation and greater disruption of this relation by a salient but irrelevant display item (color singleton distractor). Age-related differences in the covariation of intrinsic FC and cognitive performance vary as a function of task demands.     

Defensins: Natural component of human innate immunity

The widespread use of antibiotics has contributed to a huge increase in the number of resistant bacteria. New classes of drugs are therefore being developed of which defensins are a potential source. Defensins are a group of antimicrobial peptides found in different living organisms, involved in the first line of defense in their innate immune response against pathogens. This review summarizes the results of studies of this family of human antimicrobial peptides (AMPs). There is a special emphasis on describing the entire group and individual peptides, history of their discovery, their functions and expression sites. The results of the recent studies on the use of the biologically active peptides in human medicine are also presented. The pharmaceutical potential of human defensins cannot be ignored, especially considering their strong antimicrobial activity and properties such as low molecular weight, reduced immunogenicity, broad activity spectrum and resistance to proteolysis, but there are still many challenges and questions regarding the possibilities of their practical application.     

Attentional capture during visual search is attenuated by target predictability: Evidence from the N2pc,Pd, and topographic segmentation

Attentional capture by salient distractors has been confirmed by the occurrence of an N2pc to the salient distractor. To clarify some failures to replicate this finding, we varied target predictability to induce different search modes. In the unpredictable target condition, the target shape varied randomly from trial to trial, favoring singleton detection mode. In the predictable target condition, the target shape remained the same in a block of trials, favoring feature search mode. With unpredictable targets, we observed an N2pc toward the salient color distractor, confirming attentional capture in singleton search mode. With predictable targets, there was no N2pc to the salient distractor, but a distractor positivity (Pd), suggesting distractor suppression. Also, differences emerged in the topographic segmentation of N2pc and Pd. Further, the amplitude of the N2pc toward the target was larger with predictable than with unpredictable targets.     

Disulfide connectivity prediction based on structural information without a prior knowledge of the bonding state of cysteines

Previous studies predicted the disulfide bonding patterns of cysteines using a prior knowledge of their bonding states. In this study, we propose a method that is based on the ensemble support vector machine (SVM), with the structural features of cysteines extracted without any prior knowledge of their bonding states. This method is useful for improving the predictive performance of disulfide bonding patterns. For comparison, the proposed method was tested with the same dataset SPX that was adopted in previous studies. The experimental results demonstrate that bridge classification and disulfide connectivity predictions achieve 96.5% and 89.2% accuracy, respectively, using the ensemble SVM model, which outperforms the traditional method (51.5% and 51.0%, respectively) and the model that is based on a single-kernel SVM classifier (94.6% and 84.4%, respectively). For protein chain and residue classifications, the sensitivity, specificity, and accuracy of ensemble and single-kernel SVM approaches are better than those of the traditional methods. The predictive performances of the ensemble SVM and single-kernel models are identical, indicating that the ensemble model can converge to the single-kernel model for some applications.     

药物重定位候选药物筛选路径

相对传统新药研发模式,药物重定位策略发现药物新用途具有显著的成本效益优势,能加快药物上市步伐,满足恶性肿瘤、罕见病、个性化医疗等特定领域药物临床用药需求,因而被各界关注。本文主要介绍了药物重定位的一般流程与候选药物筛选路径,如从非理性设计方法向基于相似性、基于结构虚拟筛选、推理与机器学习等理性设计方法发现重定位药物的系统性转变。     

Circumspect descent prevails in solving random constraint satisfaction problems

We study the performance of stochastic local search algorithms for random instances of the K-satisfiability (K-SAT) problem. We present a stochastic local search algorithm, ChainSAT, which moves in the energy landscape of a problem instance by never going upwards in energy. ChainSAT is a focused algorithm in the sense that it focuses on variables occurring in unsatisfied clauses. We show by extensive numerical investigations that ChainSAT and other focused algorithms solve large K-SAT instances almost surely in linear time, up to high clause-to-variable ratios alpha; for example, for K = 4 we observe linear-time performance well beyond the recently postulated clustering and condensation transitions in the solution space. The performance of ChainSAT is a surprise given that by design the algorithm gets trapped into the first local energy minimum it encounters, yet no such minima are encountered. We also study the geometry of the solution space as accessed by stochastic local search algorithms.     

Rules of formation of H–C–N–O compounds at high pressure and the fates of planetary ices

The solar system’s outer planets, and many of their moons, are dominated by matter from the H–C–N–O chemical space, based on solar system abundances of hydrogen and the planetary ices H2O, CH4, and NH3. In the planetary interiors, these ices will experience extreme pressure conditions, around 5 Mbar at the Neptune mantle–core boundary, and it is expected that they undergo phase transitions, decompose, and form entirely new compounds. While temperature will dictate the formation of compounds, ground-state density functional theory allows us to probe the chemical effects resulting from pressure alone. These structural developments in turn determine the planets’ interior structures, thermal evolution, and magnetic field generation, among others. Despite its importance, the H–C–N–O system has not been surveyed systematically to explore which compounds emerge at high-pressure conditions, and what governs their stability. Here, we report on and analyze an unbiased crystal structure search among H–C–N–O compounds between 1 and 5 Mbar. We demonstrate that simple chemical rules drive stability in this composition space, which explains why the simplest possible quaternary mixture HCNO—isoelectronic to diamond—emerges as a stable compound and discuss dominant decomposition products of planetary ice mixtures.

Crystal structure prediction coupled to electronic structure calculations has emerged as a powerful tool in computational materials science, in particular in the area of high-pressure science, where it can overcome the chemical imagination attuned to ambient conditions: The predictions—and subsequent experimental confirmations—of unusual compounds such as Na2He, H3S, or LaH10 attest to the predictive power of these approaches (1–6). The planetary ices H2O, CH4, and NH3 may dominate the interiors of icy planets, but under extreme conditions (7–10). High-pressure phases of these ices have been explored computationally, and some predictions of exotic phases of individual ices have also been confirmed by experiments (11–15). Arguably, computational predictions in this field are of crucial importance because of the challenges for laboratory experiments and the indirect nature of astronomical observations. However, with increasing number of constituents the structure searches become computationally much more demanding. Hence, while structure predictions for elemental and binary systems are routine there are far fewer extensive searches of ternary systems, and none for quaternary systems.The situation in the H–C–N–O quaternary system reflects this. A vast number of publications exist on the high-pressure evolution of the individual constituents H, C, N, and O (16–19). Binary systems have also been looked at in great detail (20–24). The ternary systems are much less investigated: While H–C–O, H–N–O, and C–N–O phase diagrams have been reported (25–27), the H–C–N ternary has not, for example. The PubChem database (28) lists just under 4.8 million molecular H–C–N compounds. Overall, it contains 44.6 million H–C–N–O compounds at ambient pressure, 78% of which are of true quaternary composition—this highlights both the complexity and the relevance of this quaternary system for organic chemistry. Back in the high-pressure area, some binary mixtures of planetary ices, for instance H2O–NH3 or N2–CH4 mixtures, which form a subset of the H–N–O and H–C–N ternaries, have been studied in simulations into the megabar pressure range (29–32). However, despite the overall importance of H–C–N–O both to planetary science and Earth-bound chemical and life sciences, to our knowledge there are no computational high-pressure studies of this system, or even subsets that include all four elements, for example binary or ternary molecular mixtures such as CO2–NH3 or NH3–H2O–CH4. Here, we explore the full H–C–N–O chemical space via crystal structure searches performed at 500 GPa. This resembles the pressure—if not the temperature—at Neptune’s core–mantle boundary and therefore helps illuminate potential pressure-induced chemical reactions in the deep interiors of the outer planets and giant icy exoplanets. It also helps us understand more generally what rules govern a familiar composition space at highly unfamiliar external conditions.     

Automatic Identification of Web-Based Risk Markers for Health Events

Background

The escalating cost of global health care is driving the development of new technologies to identify early indicators of an individual’s risk of disease. Traditionally, epidemiologists have identified such risk factors using medical databases and lengthy clinical studies but these are often limited in size and cost and can fail to take full account of diseases where there are social stigmas or to identify transient acute risk factors.

Objective

Here we report that Web search engine queries coupled with information on Wikipedia access patterns can be used to infer health events associated with an individual user and automatically generate Web-based risk markers for some of the common medical conditions worldwide, from cardiovascular disease to sexually transmitted infections and mental health conditions, as well as pregnancy.

Methods

Using anonymized datasets, we present methods to first distinguish individuals likely to have experienced specific health events, and classify them into distinct categories. We then use the self-controlled case series method to find the incidence of health events in risk periods directly following a user’s search for a query category, and compare to the incidence during other periods for the same individuals.

Results

Searches for pet stores were risk markers for allergy. We also identified some possible new risk markers; for example: searching for fast food and theme restaurants was associated with a transient increase in risk of myocardial infarction, suggesting this exposure goes beyond a long-term risk factor but may also act as an acute trigger of myocardial infarction. Dating and adult content websites were risk markers for sexually transmitted infections, such as human immunodeficiency virus (HIV).

Conclusions

Web-based methods provide a powerful, low-cost approach to automatically identify risk factors, and support more timely and personalized public health efforts to bring human and economic benefits.     

Comparing image search behaviour in the ARRS GoldMiner search engine and a clinical PACS/RIS

Information search has changed the way we manage knowledge and the ubiquity of information access has made search a frequent activity, whether via Internet search engines or increasingly via mobile devices. Medical information search is in this respect no different and much research has been devoted to analyzing the way in which physicians aim to access information. Medical image search is a much smaller domain but has gained much attention as it has different characteristics than search for text documents. While web search log files have been analysed many times to better understand user behaviour, the log files of hospital internal systems for search in a PACS/RIS (Picture Archival and Communication System, Radiology Information System) have rarely been analysed. Such a comparison between a hospital PACS/RIS search and a web system for searching images of the biomedical literature is the goal of this paper. Objectives are to identify similarities and differences in search behaviour of the two systems, which could then be used to optimize existing systems and build new search engines.Log files of the ARRS GoldMiner medical image search engine (freely accessible on the Internet) containing 222,005 queries, and log files of Stanford’s internal PACS/RIS search called radTF containing 18,068 queries were analysed. Each query was preprocessed and all query terms were mapped to the RadLex (Radiology Lexicon) terminology, a comprehensive lexicon of radiology terms created and maintained by the Radiological Society of North America, so the semantic content in the queries and the links between terms could be analysed, and synonyms for the same concept could be detected. RadLex was mainly created for the use in radiology reports, to aid structured reporting and the preparation of educational material (Lanlotz, 2006) [1]. In standard medical vocabularies such as MeSH (Medical Subject Headings) and UMLS (Unified Medical Language System) specific terms of radiology are often underrepresented, therefore RadLex was considered to be the best option for this task.The results show a surprising similarity between the usage behaviour in the two systems, but several subtle differences can also be noted. The average number of terms per query is 2.21 for GoldMiner and 2.07 for radTF, the used axes of RadLex (anatomy, pathology, findings, …) have almost the same distribution with clinical findings being the most frequent and the anatomical entity the second; also, combinations of RadLex axes are extremely similar between the two systems. Differences include a longer length of the sessions in radTF than in GoldMiner (3.4 and 1.9 queries per session on average). Several frequent search terms overlap but some strong differences exist in the details. In radTF the term “normal” is frequent, whereas in GoldMiner it is not. This makes intuitive sense, as in the literature normal cases are rarely described whereas in clinical work the comparison with normal cases is often a first step.The general similarity in many points is likely due to the fact that users of the two systems are influenced by their daily behaviour in using standard web search engines and follow this behaviour in their professional search. This means that many results and insights gained from standard web search can likely be transferred to more specialized search systems. Still, specialized log files can be used to find out more on reformulations and detailed strategies of users to find the right content.