Marine fungi are an important component of pelagic planktonic communities. However, it is not yet clear how individual fungal taxa are integrated in marine processes of the microbial loop and food webs. Most likely, biotic interactions play a major role in shaping the fungal community structure.

Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics.

Following current trends for precision medicine, psychology has in recent years turned its attention to treatment personalization. Several technological and methodological advances have contributed to this renewed focus on psychology. One of these methodological advances at the center of this push toward precision medicine is network analysis. One of the core propellers of the network theory of psychopathology is the proposal that highly influential symptoms of the network (i.e., central symptoms) might be promising treatment targets. However, evidence for this proposal remains inconclusive, with evidence from idiographic longitudinal assessments lacking. In this study, we explore the impact of symptom deactivation in individual networks (named idiographic networks). We tested two types of symptom deactivation: normal and cascade attack, and five measures for highly influential symptom identification (degree, strength, eigenvector, expected influence, and random attack condition). We find that a cascade degree-based attack is more effective at deactivating the symptom network, we next discuss the implications for treatment personalization and precision psychology.

The increase in human population has fueled demand for pollination services; the resulting intensification and globalization of honey bee management has coincided with increased pathogen pressure. We hypothesized that Israeli acute paralysis virus (IAPV) can alter host social behavior, predicting different behavioral changes depending on social context.

Abstract Network analyses, such as of gene co-expression networks, metabolic networks and ecological networks have become a central approach for the systems-level study of biological data. Several software packages exist for generating and analyzing such networks, either from correlation scores or the absolute value of a transformed score called weighted topological overlap (wTO). However, since gene regulatory processes can up- or down-regulate genes, it is of great interest to explicitly consider both positive and negative correlations when constructing a gene co-expression network.

Using RNA-induced-silencing-complex precipitation, we identified 98 high-confidence miR-124 targets, of which some directly led to decreased viability. By performing advanced transcription-factor-network analysis, we identified indirect miR-124 effects on apoptosis, neuronal subtype differentiation, and the regulation of previously uncharacterized zinc finger transcription factors.

Abstract Despite the importance of hand hygiene in the health care setting, there are no studies evaluating hand hygiene compliance at hospital entrances. The study was prospectively performed over a 33-week period from March 30, 2014-November 15, 2014, to evaluate hand hygiene compliance in 2 hospital reception areas. We compared electronic handwash counters with the application of radiofrequency identification (GOJO SMARTLINK) (electronic observer) that counts each activation of alcohol gel dispensers to direct observation (human observer) via remote review of video surveillance.