Seasonal changes in energy expenditure, body temperature and activity patterns in llamas (Lama glama)

The authors thank Knut Salzmann und Arne Oppermann for technical help and for taking care of the animals and Anna Stölzl for help with the administering of the ruminal unit of the telemetry system. The study was supported by a grant from the German Research Foundation (DFG) to A.R. (RI 1796/3-1).Peer reviewedPublisher PD

EmoLabel: Semi-Automatic Methodology for Emotion Annotation of Social Media Text

The exponential growth of the amount of subjective information on the Web 2.0. has caused an increasing interest from researchers willing to develop methods to extract emotion data from these new sources. One of the most important challenges in textual emotion detection is the gathering of data with emotion labels because of the subjectivity of assigning these labels. Basing on this rationale, the main objective of our research is to contribute to the resolution of this important challenge. This is tackled by proposing EmoLabel: a semi-automatic methodology based on pre-annotation, which consists of two main phases: (1) an automatic process to pre-annotate the unlabelled English sentences; and (2) a manual process of refinement where human annotators determine which is the dominant emotion. Our objective is to assess the influence of this automatic pre-annotation method on manual emotion annotation from two points of view: agreement and time needed for annotation. The evaluation performed demonstrates the benefits of pre-annotation processes since the results on annotation time show a gain of near 20% when the pre-annotation process is applied (Pre-ML) without reducing annotator performance. Moreover, the benefits of pre-annotation are higher in those contributors whose performance is low (inaccurate annotators).This research has been supported by the Spanish Government (ref. RTI2018-094653-B-C22) and the Valencian Government (grant no. PROMETEU/2018/089). It has also been funded by the FPI grant (BES-2013-065950) and the research stay grant (EEBB-I-17-12578) from the Spanish Ministry of Science and Innovation

Multispectral LIF-Based Standoff Detection System for the Classification of CBE Hazards by Spectral and Temporal Features

Laser-induced fluorescence (LIF) is a well-established technique for monitoring chemical processes and for the standoff detection of biological substances because of its simple technical implementation and high sensitivity. Frequently, standoff LIF spectra from large molecules and bio-agents are only slightly structured and a gain of deeper information, such as classification, let alone identification, might become challenging. Improving the LIF technology by recording spectral and additionally time-resolved fluorescence emission, a significant gain of information can be achieved. This work presents results from a LIF based detection system and an analysis of the influence of time-resolved data on the classification accuracy. A multi-wavelength sub-nanosecond laser source is used to acquire spectral and time-resolved data from a standoff distance of 3.5 m. The data set contains data from seven different bacterial species and six types of oil. Classification is performed with a decision tree algorithm separately for spectral data, time-resolved data and the combination of both. The first findings show a valuable contribution of time-resolved fluorescence data to the classification of the investigated chemical and biological agents to their species level. Temporal and spectral data have been proven as partly complementary. The classification accuracy is increased from 86% for spectral data only to more than 92%

Application of Standoff LIF to Living and Inactivated Bacteria Samples

To minimize the impact of an airborne bio-agent output, sensitive, specific and swift detection and identification are essential. A single method can hardly meet all of these requirements. Point sensors allow highly sensitive and specific identification but are localized and comparatively slow. Most laser-based standoff systems lack selectivity and specificity but provide real-time detection and classification in a wide region with additional information about location and propagation. A combination of both methods allows benefiting from their complementary assets and may be a promising solution to optimize detection and identification of hazardous substances. Here, we present progress for an outdoor bio-detector based on laser-induced fluorescence (LIF) developed at the DLR Lampoldshausen. After excitation at 280 and 355 nm, bacteria species express unique fluorescence spectra. Upon deactivation, the spectral features change depending on the applied method

Vasodilator-Stimulated Phosphoprotein (VASP)-dependent and -independent pathways regulate thrombin-induced activation of Rap1b in platelets

BACKGROUND: Vasodilator-Stimulated Phosphoprotein (VASP) is involved in the inhibition of agonist-induced platelet aggregation by cyclic nucleotides and the adhesion of platelets to the vascular wall. α(IIb)β(3) is the main integrin responsible for platelet activation and Rap1b plays a key role in integrin signalling. We investigated whether VASP is involved in the regulation of Rap1b in platelets since VASP-null platelets exhibit augmented adhesion to endothelial cells in vivo. METHODS: Washed platelets from wild type and VASP-deficient mice were stimulated with thrombin, the purinergic receptors agonist ADP, or the thromboxane A2 receptor agonist U46619 and Rap1b activation was measured using the GST-RalGDS-RBD binding assay. Interaction of VASP and Crkl was investigated by co-immunoprecipitation, confocal microscopy, and pull-down assays using Crkl domains expressed as GST-fusion proteins. RESULTS: Surprisingly, we found that activation of Rap1b in response to thrombin, ADP, or U46619 was significantly reduced in platelets from VASP-null mice compared to platelets from wild type mice. However, inhibition of thrombin-induced activation of Rap1b by nitric oxide (NO) was similar in platelets from wild type and VASP-null mice indicating that the NO/cGMP/PKG pathway controls inhibition of Rap1b independently from VASP. To understand how VASP regulated Rap1b, we investigated association between VASP and the Crk-like protein (Crkl), an adapter protein which activates the Rap1b guanine nucleotide exchange factor C3G. We demonstrated the formation of a Crkl/VASP complex by showing that: 1) Crkl co-immunoprecipitated VASP from platelet lysates; 2) Crkl and VASP dynamically co-localized at actin-rich protrusions reminiscent of focal adhesions, filopodia, and lamellipodia upon platelet spreading on fibronectin; 3) recombinant VASP bound directly to the N-terminal SH3 domain of Crkl; 4) Protein Kinase A (PKA) -mediated VASP phosphorylation on Ser157 abrogated the binding of Crkl. CONCLUSIONS: We identified Crkl as a novel protein interacting with VASP in platelets. We propose that the C3G/Crkl/VASP complex plays a role in the regulation of Rap1b and this explains, at least in part, the reduced agonist-induced activation of Rap1b in VASP-null platelets. In addition, the fact that PKA-dependent VASP phosphorylation abrogated its interaction with Crkl may provide, at least in part, a rationale for the PKA-dependent inhibition of Rap1b and platelet aggregation

Regulating craving by anticipating positive and negative outcomes : a multivariate pattern analysis and network connectivity approach

During self-control, we may resist short-term temptations in order to reach a favorable future (e.g., resisting cake to stay healthy). The neural basis of self-control is typically attributed to “cold,” unemotional cognitive control mechanisms which inhibit affect-related regions via the prefrontal cortex (PFC). Here, we investigate the neural underpinnings of regulating cravings by mentally evoking the positive consequences of resisting a temptation (e.g., being healthy) as opposed to evoking the negative consequences of giving in to a temptation (e.g., becoming overweight). It is conceivable that when using these types of strategies, regions associated with emotional processing [e.g., striatum, ventromedial prefrontal cortex (vmPFC)] are involved in addition to control-related prefrontal and parietal regions. Thirty-one participants saw pictures of unhealthy snacks in the fMRI scanner and, depending on the trial, regulated their craving by thinking of the positive consequences of resisting, or the negative consequences of not resisting. In a control condition, they anticipated the pleasure of eating and thus, allowed the craving to occur (now-condition). In line with previous studies, we found activation of a cognitive control network during self-regulation. In the negative future thinking condition, the insula was more active than in the positive condition, while there were no activations that were stronger in the positive (> negative) future thinking condition. However, additionally, multivariate pattern analysis showed that during craving regulation, information about the valence of anticipated emotions was present in the vmPFC, the posterior cingulate cortex (PCC) and the insula. Moreover, a network including vmPFC and PCC showed higher connectivity during the positive (> negative) future thinking condition. Since these regions are often associated with affective processing, these findings suggest that “hot,” affective processes may, at least in certain circumstances, play a role in self-control

Conceptual design for an ultra-sensitive bioaerosol detection system

The detection of aerosols in general and bioaerosols more specific has gained an increased importance in multiple fields. While environmental scientists are increasingly interested in the impacts of aerosols onto climatic effects, researchers in the security sector are looking for ways to remotely detect dangerous substances from safe distances. Additionally, due to the Corona pandemic, the detection of bioaerosols has gained significant relevance in sectors like public health, transportation, and aviation. As a result, more accurate, i.e. sensitive and specific, measurement equipment is needed. Here we present the design concept for a new sensor system designed to measure thin bioaerosol clouds. For the detection air samples are excited with laser light to generate a signal based on laser induced fluorescence. The fluorescence is collected in an integration sphere to optimize signal. Inside the integration sphere multiple sensors are placed, each combined with a filter to exclude all signals not belonging to a certain, agent specific wavelength interval. Through the intelligent combination of spectral intervals, a specific characteristic of the studied air sample is measured. Based on the measured characteristic a classification is performed to determine the category of the sample. Development aims at testing indoor air quality in real time

The phosphoproteome of choroid plexus epithelial cells following infection with Neisseria meningitidis

The Gram-negative bacterium Neisseria meningitidis, which causes meningitis in humans, has been demonstrated to manipulate or alter host signalling pathways during infection of the central nervous system (CNS). However, these complex signalling networks are not completely understood. We investigate the phosphoproteome of an in vitro model of the blood-cerebrospinal fluid barrier (BCSFB) based on human epithelial choroid plexus (CP) papilloma (HIBCPP) cells during infection with the N. meningitidis serogroup B strain MC58 in presence and absence of the bacterial capsule. Interestingly, our data demonstrates a stronger impact on the phosphoproteome of the cells by the capsule-deficient mutant of MC58. Using enrichment analyses, potential pathways, molecular processes, biological processes, cellular components and kinases were determined to be regulated as a consequence of N. meningitidis infection of the BCSFB. Our data highlight a variety of protein regulations that are altered during infection of CP epithelial cells with N. meningitidis, with the regulation of several pathways and molecular events only being detected after infection with the capsule-deficient mutant. Mass spectrometry proteomics data are available via ProteomeXchange with identifier PXD038560