Exploring modality switching effects in negated sentences: further evidence for grounded representations

Theories of embodied cognition (e.g., Perceptual Symbol Systems Theory; Barsalou, 1999, 2009) suggest that modality specific simulations underlie the representation of concepts. Supporting evidence comes from modality switch costs: participants are slower to verify a property in one modality (e.g., auditory, BLENDER-loud) after verifying a property in a different modality (e.g., gustatory, CRANBERRIES-tart) compared to the same modality (e.g., LEAVES-rustling, Pecher et al., 2003). Similarly, modality switching costs lead to a modulation of the N400 effect in event-related potentials (ERPs; Collins et al., 2011; Hald et al., 2011). This effect of modality switching has also been shown to interact with the veracity of the sentence (Hald et al., 2011). The current ERP study further explores the role of modality match/mismatch on the processing of veracity as well as negation (sentences containing “not”). Our results indicate a modulation in the ERP based on modality and veracity, plus an interaction. The evidence supports the idea that modality specific simulations occur during language processing, and furthermore suggest that these simulations alter the processing of negation

Asymmetric activation of the anterior cerebral cortex in recipients of IRECA: preliminary evidence for the energetic effects of an intention-based treatment modality on human neurophysiology.

Objectives: Neurophysiologic studies of mindfulness link the health benefits of meditation to activation of the left-anterior cerebral cortex. The similarity and functional importance of intention and attentional stance in meditative and biofield therapeutic practices suggest that modulation of recipient anterior asymmetric activation may mediate the energetic effects of intention-based biofield treatments as well. The aim of the current study was to test this hypothesis by using a treatment modality known as IRECA (Istituto di Ricerca sull'Energia Cosmica Applicata). Design: Participants' electroencephalograms (EEG) were recorded over a 5-minute recovery period (subdivided into three 100-second intervals) while participants received genuine IRECA, placebo treatment, or no treatment, after completion of a cognitively demanding task. Participants: 21 undergraduate students (3 men and 18 women; mean age, 22.1 years). All were right-handed and none had a history of neurologic or psychological impairment. Outcome measures: (1) Alpha Asymmetry Index (AAI), a standard measure of anterior asymmetric activation of the cerebral cortex, defined as the average right hemisphere minus left hemisphere log alpha power of EEG recordings for homologous pairs of electrodes in frontal and prefrontal regions; (2) self-report measures of state anxiety obtained at baseline, before treatment, and after treatment, using a short form of the State-Trait Anxiety Inventory. Results: In line with predictions, recipients of IRECA showed enhanced left-anterior activation of the cerebral cortex relative to placebo and no-treatment controls (as indicated by significantly higher and significantly positive AAI scores) during the first 100 seconds of treatment, and they reported greater overall reduction in state anxiety relative to baseline measures. Conclusions: The current study provides preliminary supporting evidence for an intention-based biofield therapeutic modality offsetting the negative effects of stress via sympathetic activation of recipients' left-anterior cerebral cortex

Modality switching and negation: ERP evidence for modality-specific simulations during negation processing

The Perceptual Symbol System Theory of cognition (Barsalou, 1999) suggests that modality-specific simulations underlie representation of concepts. This is evidenced by processing costs for switching modalities. That is, participants are slower to verify a property in the auditory modality (e.g., BLENDER-loud) after verifying a property in a different modality (e.g., CRANBERRIES-tart) and faster when verifying a property in the same modality (e.g., LEAVES-rustling). The modality switch cost has also been shown to lead to a modulation of the N400 event-related potential (ERP) (Collins, Pecher, Zeelenberg & Coulson, 2011 using a property verification task; Hald, Marshall, Janssen & Garnham, 2011 using a sentence verification task). In a separate line of research, ERP studies have indicated that without a discourse context, negated sentences are more difficult to process than affirmative sentences, leading to a different N400 pattern for negative sentences than for affirmative sentences (e.g., Fischler, Bloom, Childers, Roucos, & Perry, 1983.) Unlike affirmative sentences, sentences containing negation show a larger N400 for correct, semantically coherent single sentences (i.e., factually true sentences) than for semantically incorrect sentences (i.e., false sentences). However, Nieuwland and Kuperberg (2008,) found that the pragmatics of the sentence can change this N400 pattern to one closer to affirmative sentences. The goal of the current study was to explore whether the processing of negation could be aided by modality matching information. Other evidence suggests that comprehenders create a simulation of negative sentences (Kaup, Yaxley, Madden, Zwaan, & Lüdtke, 2007), but it is unclear whether modality matching information could modulate the processing cost of negation. Essentially, can modality matching information as reported by Collins et al., (2011) and Hald et al., (2011) lead to a modulation of the N400 for true negated sentences similar to that seen when discourse pragmatics supports negation? Furthermore, we were interested in whether the modality switch effect would lead to a similar pattern in the ERPs as that found with affirmative sentences (Collins et al., 2011 & Hald et al., 2011). Using a within-subjects design we used 160 pairs of experimental pairs which were either of the same or of a different modality. All experimental items were either visual or tactile modality and were drawn from existing sets of materials (Pecher, et al., 2003; Van Dantzig, et al., 2008). For example, a different modality pair was “A light bulb is very hot” followed by “Rice isn’t black” versus a same visual modality pair “A giraffe is spotted” followed by “Rice isn’t black”. We predicted that the underlined word is where a modulation in the N400 may be seen. Additionally, we explored veracity by making half of the experimental target sentences false (“Rice isn’t white”). Participants were asked to judge whether each sentence was typically true or false. Our initial results indicate a modulation in the ERP based on both modality and veracity. For true (“Rice isn’t black”) and false target statements (“Rice isn’t white”) different modality pairs elicit a larger frontal-central N400 like effect compared to same modality pairs (Figure 1), replicating Hald et al., (2011). When comparing true versus false, the different modality pairs elicit a large posterior N400 for true compared to false sentences (replicating the effect for negated sentences, i.e., Fischler et al., 1983). However for same modality pairs there is a reduction in the N400 to true statements; no difference is seen between true and false statements in the ERP (Figure 2). These results replicate and extend previous ERP findings using the modality switch paradigm. The evidence suggests that not only do modality-specific simulations occur but they can even aid the processing of negation

Editorial: Integrating Whole Genome Sequencing Into Source Attribution and Risk Assessment of Foodborne Bacterial Pathogens

Source attribution and microbial risk assessment have proved to be crucial to identify and prioritize food safety interventions as to effectively control the burden of human illnesses (Cassini et al., 2016; Mughini-Gras et al., 2018a, 2019). By comparing human cases and pathogen occurrences in selected animal, food, and environmental sources, microbial subtyping approaches were successfully applied to pinpoint the most important sources of Salmonella, Campylobacter, Shiga toxin-producing Escherichia coli, and Listeria monocytogenes (Hald et al., 2004; Mullner et al., 2009a,b; Barco et al., 2013; Nielsen et al., 2017; Mughini-Gras et al., 2018b; Cody et al., 2019). Microbial risk assessment has been applied to assess known or potential adverse health effects resulting from human exposure to food-borne hazards. Through a scientific structured approach (FAO and WHO, 2021), microbial risk assessment helps to identify and quantify the risk represented by specific foods and the critical points in these foods' production chains for microbial control (Cassini et al., 2016; FAO and WHO, 2021). For both source attribution and risk assessment, one key challenge has been to define the hazard in question: is the whole foodborne pathogen species a hazard, or only some of its subtypes? In this regard the choice of the subtyping method becomes crucial. In recent years, Whole Genome Sequencing (WGS) has represented a major benefit for more targeted approaches, no longer focused on the species/genus level but at the level of subtypes (Franz et al., 2016; Fritsch et al., 2018; EFSA Panel on Biological Hazards, 2019). Besides WGS, metagenomics showed potentialities in source attribution. In particular, this approach was useful in attributing the source of environmental contamination by comparing the abundances of source-specific genetic markers (i.e., resistome) in different reservoirs (Gupta et al., 2019). Therefore, this special issue focuses on traditional and novel source attribution approaches applied on molecular, WGS, and metagenomic data as well as on a fine-tuning genetic characterization of foodborne pathogens useful for hazard identification and characterization. In particular, one study compares the outputs of a modified Hald model, which was applied to different subtyping input data of S. enterica Typhimurium and its monophasic variant (Arnold et al.) whereas two studies proposed a novel network approach and a method based on the core-genome genetic distance to attribute human infections of S. enterica Typhimurium monophasic variant and S. enterica Derby using WGS as input data (Merlotti et al.; Sévellec et al.). Another study by Duarte et al. included the relative abundance of antimicrobial resistance (AMR) associated genes (resistome) as metagenomic input data in an AMR source attribution study. Finally, two studies were focused on the molecular and genomic characterization of human isolates of Campylobacter jejuni and C. coli from China and of Listeria monocytogenes isolates collected from ready-to-eat meat and processing environment from Poland (Zhang et al.; Kurpas et al.). Arnold et al. performed a source attribution study including the genomes of S. enterica Typhimurium and its monophasic variant of 596 human sources and 327 animal sources from England and Wales between 2014 and 2016. Data from Seven Loci Multi Locus Sequence Typing (7-loci MLST), core-genome MLST (cg-MLST), and SNP calling were compared as input data. By applying a modified Hald model, 60% of human genomes were attributed to pork. Comparing different input data, results highlighted MLST as the method with the lowest fit and the lowest discriminatory power. Merlotti et al. applied a network approach to 351 human and animal genomes of S. enterica Typhimurium and its monophasic variant collected from 2013 to 2014. Three datasets of whole-genome MLST (wgMLST), cgMLST, and SNPs were used as input data. Genomes were clustered based on their genetic similarities. Interestingly, a higher percentage of cluster coherence was reported for animal sources in comparison to country and year of isolation, suggesting animal sources as the major driver of cluster formation. The approach showed to be effective in attributing up to 97.2% of human genomes to animal sources represented in the dataset. Among these genomes, the majority (84%) was attributed to pigs/pork. No significant differences were highlighted by comparing the three different input datasets. Core genome analysis was the approach applied by Sévellec et al. to attribute human sporadic cases of S. enterica Derby that occurred in France in 2014–2015 to non-human reservoirs. The authors analyzed 299 S. enterica Derby genomes corresponding to all S. enterica Derby sporadic human cases registered in the time frame, along with 141 non-human genomes. Within the non-human genomes, three main genomic lineages were detected in France: ST39-ST40 and ST682 associated to pork and ST71 associated to poultry. Within human genomes, 94% of S. enterica Derby clustered within the three genetic groups associated with pork, identifying this animal reservoir as the major contributor of S. enterica Derby to sporadic human cases in France. Relative abundance of antimicrobial resistance genes in shotgun metagenomic data was chosen in an antimicrobial resistance source attribution study by Duarte et al.. Starting from the assumption that fecal resistomes are source related, authors compared the resistomes of pooled fecal samples of pigs, broilers, turkeys, and veal calves with the resistomes of individual fecal samples of humans occupationally exposed to livestock production. Five supervised random forest models were applied on a total of 479 observations. Among the four livestock species, the results indicated that pigs have the resistome composition closest to the composition of the human resistome suggesting that occupational exposure to AMR determinants was higher among workers exposed to pigs than workers of broiler farms. Zhang et al. characterized genetic diversity and antimicrobial resistance of 236 Campylobacter jejuni and C. coli isolates collected from 2,945 individual stool samples of hospitalized patients with diarrhea in Beijing from 2017 to 2018. MLST results confirmed the high genetic diversity among isolates as well as CC21 as the most common clonal complex of C. jejuni in diarrhea patients in China. Clonal complex CC828 was the most frequently identified among C. coli isolates. Regarding antimicrobial resistance, rates higher than 88% were identified for the antimicrobials nalidixic acid, ciprofloxacin, and tetracycline. Last but not least, Kurpas et al. genetically characterized 48 L. monocytogenes isolates of PCR-serogroup IIb and IVb collected from ready-to-eat food and food processing environments. Additionally, the authors compared them with public genomes collected from humans in Poland. Among food isolates, 65% belonged to CC1, CC2, and CC6 already described as hypervirulent strains in humans. The clonal complex CC5 was also identified; mostly collected from food processing environments and belonging to PCR-serogroup IIB. Genomes of this clonal complex showed mutations in the inlA gene and a deletion of 144 bp in the inlB gene suggesting them as hypovirulent. Based on these studies, we conclude that the application of NGS data, in particular source attribution models, shows great potential. The results are improved by becoming more specific and to the point, which is considered very valuable for the decision support process. Integrations with phenotypic tests will continue to be essential for confirmation of NGS predicted outcomes

Efficient polarization squeezing in optical fibers

We report on a novel and efficient source of polarization squeezing using a single pass through an optical fiber. Simply passing this Kerr squeezed beam through a carefully aligned lambda/2 waveplate and splitting it on a polarization beam splitter, we find polarization squeezing of up to 5.1 +/- 0.3 dB. The experimental setup allows for the direct measurement of the squeezing angle.Comment: 4 pages, 4 figure

LPS Counter Regulates RNA Expression of Extracellular Proteases and Their Inhibitors in Murine Macrophages

Besides their evident importance in host defense, macrophages have been shown to play a detrimental role in different pathological conditions, including chronic inflammation, atherosclerosis, and cancer. Regardless of the exact situation, macrophage activation and migration are intimately connected to extracellular matrix degradation. This process is accomplished by multiple proteolytic enzymes, including serine proteases and members of the matrix metalloproteinase family. In this study, we have utilized qPCR arrays to simultaneously analyze the temporal expression pattern of a range of genes involved in extracellular matrix metabolism in the mouse derived-macrophage cell line RAW 264.7 following stimulation with LPS. Our results revealed that LPS induces the expression of matrix metalloproteinases while at the same time decreased the expression of matrix metalloproteinase inhibitors. The opposite scenario was found for the genes encoding serine proteases, which were downregulated while their inhibitors were upregulated. In addition, intergenic comparison of the expression levels of related proteases revealed large differences in their basal expression level. These data highlight the complexity of the gene expression regulation implicated in macrophage-dependent matrix degradation and furthermore emphasize the value of qPCR array techniques for the investigation of the complex regulation of the matrix degradome

A farm transmission model for Salmonella in pigs for individual EU Member States

The burden of Salmonella entering pig slaughterhouses across the European Union (EU) is considered to be of public health significance. Therefore, targets will be set for each EU Member State (MS) to reduce the prevalence of Salmonella in pigs at slaughter. As part of the evidence base for the development of National Control Plans (NCPs), a Quantitative Microbiological Risk Assessment (QMRA) was funded to support the scientific opinion required by the EC from the European Food Safety Authority, and subsequently adopted by the BIOHAZ panel

Three-dimensional theory for interaction between atomic ensembles and free-space light

Atomic ensembles have shown to be a promising candidate for implementations of quantum information processing by many recently-discovered schemes. All these schemes are based on the interaction between optical beams and atomic ensembles. For description of these interactions, one assumed either a cavity-QED model or a one-dimensional light propagation model, which is still inadequate for a full prediction and understanding of most of the current experimental efforts which are actually taken in the three-dimensional free space. Here, we propose a perturbative theory to describe the three-dimensional effects in interaction between atomic ensembles and free-space light with a level configuration important for several applications. The calculations reveal some significant effects which are not known before from the other approaches, such as the inherent mode-mismatching noise and the optimal mode-matching conditions. The three-dimensional theory confirms the collective enhancement of the signal-to-noise ratio which is believed to be one of the main advantage of the ensemble-based quantum information processing schemes, however, it also shows that this enhancement need to be understood in a more subtle way with an appropriate mode matching method.Comment: 16 pages, 9 figure