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Background: In this review, we introduce the displacement encoding with stimulated echoes (DENSE) method for measuring myocardial dyssynchrony using cardiovascular magnetic resonance (CMR) imaging. We provide an overview of research findings related to DENSE from the past two decades and discuss other techniques used for dyssynchrony evaluation. Additionally, the review discusses the potential uses of DENSE in clinical practice. Methods: A search was conducted to identify relevant articles published from January 2000 through January 2023 using the Scopus, Web of Science, PubMed and Cochrane databases. The following search term was used: (DENSE OR ‘displacement encoding with stimulated echoes’ OR CURE) AND (dyssynchrony* OR asynchron* OR synchron*) AND (MRI OR ‘magnetic resonance’ OR CMR). Results: After removing duplicates, researchers screened a total of 174 papers. Papers that were not related to the topic, reviews, general overview articles and case reports were excluded, leaving 35 articles for further analysis. Of these, 14 studies focused on cardiac dyssynchrony estimation with DENSE, while the remaining 21 studies served as background material. The studies used various methods for presenting synchronicity, such as circumferential uniformity ratio estimate (CURE), CURE-singular value decomposition (SVD), radial uniformity ratio estimate (RURE), longitudinal uniformity ratio estimate (LURE), time to onset of shortening (TOS) and dyssynchrony index (DI). Most of the dyssynchrony studies concentrated on human heart failure, but congenital heart diseases and obesity were also evaluated. The researchers found that DENSE demonstrated high reproducibility and was found useful for detecting cardiac resynchronisation therapy (CRT) responders, optimising CRT device settings and assessing right ventricle synchronicity. In addition, studies showed a correlation between cardiac fibrosis and mechanical dyssynchrony in humans, as well as a decrease in the synchrony of contraction in the left ventricle in obese mice. Conclusions: DENSE shows promise as a tool for quantifying myocardial function and dyssynchrony, with advantages over other cardiac dyssynchrony evaluation methods. However, there remain challenges related to DENSE due to the relatively time-consuming imaging and analysis process. Improvements in imaging and analysing technology, as well as possible artificial intelligence solutions, may help overcome these challenges and lead to more widespread clinical use of DENSE.

Highlights In a focal rat DTH-EAE model of neuroinflammation, dimethyl fumarate decreases the uptake of TSPO PET tracer [18F]GE-180 in the short term. Long-term [18F]GE-180 follow-up did not indicate a treatment effect. Decreased neuroinflammation, CD4+ T cell infiltration, and CD8+ T cell infiltration were detected using immunohistochemistry.

Abstract Background Mindfulness-based interventions (MBIs) have been used in oncology contexts as a promising tool with numerous benefits for various health-related and psychosocial outcomes. Despite the increasing popularity of MBIs, few randomized controlled trials (RCTs) have examined their effects upon biological parameters. Specifically, no previous study has examined the effects of MBIs on extracellular vesicles (EVs), which are potentially important markers of health, disease, and stress. Moreover, the lack of RCTs is even more limited within the context of technology-mediated MBIs and long-term effects. Methods The current study protocol presents a two-arm, parallel, randomized controlled study investigating the effects of internet-supported mindfulness-based cognitive therapy (MBCT) compared with treatment as usual (TAU). Primary outcomes are psychological distress and EV cargo of distressed participants with previous breast, colorectal, or prostate cancer diagnoses. Secondary outcomes are self-reported psychosocial and health-related measures, and additional biological markers. Outcomes will be assessed at baseline, 4 weeks after baseline (mid-point of the intervention), 8 weeks after baseline (immediately post-intervention), 24 weeks after baseline (after booster sessions), and 52 weeks after baseline. Our goal is to recruit at least 111 participants who have been diagnosed with breast, prostate, or colorectal cancer (cancer stage I to III), are between 18 and 65 years old, and have had primary cancer treatments completed between 3 months and 5 years ago. Half of the participants will be randomized to the TAU group, and the other half will participate in an 8-week online MBCT intervention with weekly group sessions via videoconference. The intervention also includes asynchronous homework, an online retreat after the fifth week, and 4 monthly booster sessions after completion of the 8-week programme. Discussion This study will allow characterizing the effects of internet-based MBCT on psychosocial and biological indicators in the context of cancer. The effects on circulating EVs will also be investigated, as a possible neurobiological pathway underlying mind-body intervention effects. Trial registration ClinicalTrials.gov NCT04727593 (date of registration: 27 January 2021; date of record verification: 6 October 2021).

Abstract Background The emergence of antimicrobial resistance (AMR) among bacterial pathogens demands a local understanding of the epidemiological situation. This information is needed both for clinical treatment decision-making purposes as well as for the revision of current care guidelines. Clinical AMR data from Namibia is sparse, whilst urinary tract infections remain not only widespread but they disproportionally affect females. This paper aims to describe the national antimicrobial resistance situation of major bacterial uropathogens in females within the 14 Namibian regions. Method Retrospective countrywide information on clinical urine cultures performed in females in Namibia in 2016–2017 was obtained from the national public health laboratory, Namibia Institute of Pathology (NIP). The data set included both microbiological findings as well as antimicrobial susceptibility test (AST) results. The AST was done as per the Clinical and Laboratory Standards Institute (CLSI) guidelines. Resistance to 3rd generation cephalosporins was indicative of Extended Spectrum-ß-lactamase (ESBL) production. Data analysis was done with WHONET using expert interpretation rules. Results In total, 22,259 urinary cultures were performed, of which 13,673 (61.4%) were culture positive. Gram-negative bacterial species accounted for 72.6% of the findings. The most common pathogens identified were Escherichia coli, Klebsiella pneumoniae and Proteus mirabilis. Most of these were from young females, with a median age ranging from 28 to 32 years for the various pathogens. Resistance to ampicillin was 77.7% in E. coli and 84.9% in K. pneumoniae. In E. coli, resistance to 1st line empiric therapy antibiotic, nitrofurantoin, was below 13%, except for one region that showed 59.2% resistance. Resistance to third generation cephalosporin (3GC) was used as a proxy for ESBL production. By year 2017, 3GC resistance was 22%, 31.4% and 8.3% for E. coli, K. pneumoniae and P. mirabilis, respectively. Conclusion We report high resistance to ampicillin, quinolones and sulfamethoxazole-trimethoprim amongst E. coli. Resistance rates to third-generation cephalosporins was also concerningly high at 22%. Resistance to carbapenems was low. However, superiority of nitrofurantoin was found, which provides rational support for the usefulness of nitrofurantoin as an empiric therapy regimen for the treatment of urinary tract infections in this setting.

Abstract Background Kuwait had its first COVID-19 in late February, and until October 6, 2020 it recorded 108,268 cases and 632 deaths. Despite implementing one of the strictest control measures-including a three-week complete lockdown, there was no sign of a declining epidemic curve. The objective of the current analyses is to determine, hypothetically, the optimal timing and duration of a full lockdown in Kuwait that would result in controlling new infections and lead to a substantial reduction in case hospitalizations. Methods The analysis was conducted using a stochastic Continuous-Time Markov Chain (CTMC), eight state model that depicts the disease transmission and spread of SARS-CoV 2. Transmission of infection occurs between individuals through social contacts at home, in schools, at work, and during other communal activities. Results The model shows that a lockdown 10 days before the epidemic peak for 90 days is optimal but a more realistic duration of 45 days can achieve about a 45% reduction in both new infections and case hospitalizations. Conclusions In the view of the forthcoming waves of the COVID19 pandemic anticipated in Kuwait using a correctly-timed and sufficiently long lockdown represents a workable management strategy that encompasses the most stringent form of social distancing with the ability to significantly reduce transmissions and hospitalizations.

Abstract Background Surveillance is the cornerstone of surgical site infection prevention programs. The validity of the data collection and awareness of vulnerability to inter-rater variation is crucial for correct interpretation and use of surveillance data. The aim of this study was to investigate the reliability and validity of surgical site infection (SSI) surveillance after colorectal surgery in the Netherlands. Methods In this multicentre prospective observational study, seven Dutch hospitals performed SSI surveillance after colorectal surgeries performed in 2018 and/or 2019. When executing the surveillance, a local case assessment was performed to calculate the overall percentage agreement between raters within hospitals. Additionally, two case-vignette assessments were performed to estimate intra-rater and inter-rater reliability by calculating a weighted Cohen’s Kappa and Fleiss’ Kappa coefficient. To estimate the validity, answers of the two case-vignettes questionnaires were compared with the answers of an external medical panel. Results 1111 colorectal surgeries were included in this study with an overall SSI incidence of 8.8% (n = 98). From the local case assessment it was estimated that the overall percent agreement between raters within a hospital was good (mean 95%, range 90–100%). The Cohen’s Kappa estimated for the intra-rater reliability of case-vignette review varied from 0.73 to 1.00, indicating substantial to perfect agreement. The inter-rater reliability within hospitals showed more variation, with Kappa estimates ranging between 0.61 and 0.94. In total, 87.9% of the answers given by the raters were in accordance with the medical panel. Conclusions This study showed that raters were consistent in their SSI-ascertainment (good reliability), but improvements can be made regarding the accuracy (moderate validity). Accuracy of surveillance may be improved by providing regular training, adapting definitions to reduce subjectivity, and by supporting surveillance through automation.

The Solar MAgnetic Connection HAUS1 tool (Solar-MACH) is an open-source tool completely written in Python that derives and visualizes the spatial configuration and solar magnetic connection of different observers (i.e., spacecraft or planets) in the heliosphere at different times. For doing this, the magnetic connection in the interplanetary space is obtained by the classic Parker Heliospheric Magnetic Field (HMF). In close vicinity of the Sun, a Potential Field Source Surface (PFSS) model can be applied to connect the HMF to the solar photosphere. Solar-MACH is especially aimed at providing publication-ready figures for the analyses of Solar Energetic Particle events (SEPs) or solar transients such as Coronal Mass Ejections (CMEs). It is provided as an installable Python package (listed on PyPI and conda-forge), but also as a web tool at solar-mach.github.io that completely runs in any web browser and requires neither Python knowledge nor installation. The development of Solar-MACH is open to everyone and takes place on GitHub, where the source code is publicly available under the BSD 3-Clause License. Established Python libraries like sunpy and pfsspy are utilized to obtain functionalities when possible. In this article, the Python code of Solar-MACH is explained, and its functionality is demonstrated using real science examples. In addition, we introduce the overarching SERPENTINE project, the umbrella under which the recent development took place.

How thermal particles are accelerated to suprathermal energies is an unsolved issue, crucial for many astrophysical systems. We report novel observations of irregular, dispersive enhancements of the suprathermal particle population upstream of a high-Mach-number interplanetary shock. We interpret the observed behavior as irregular “injections” of suprathermal particles resulting from shock front irregularities. Our findings, directly compared to self-consistent simulation results, provide important insights for the study of remote astrophysical systems where shock structuring is often neglected.

Abstract Metastases of distant primary tumors on the parotid gland are very rare. Tumor‐to‐tumor metastasis to salivary gland tumors is extremely rare. A case of a 69‐year‐old woman with a large left parotid gland mass with no previous salivary gland problems or cancer. Fine‐needle aspiration (FNA) showed evidence of a Warthin tumor. A total left parotidectomy was performed. The final pathology report showed a Warthin tumor containing two metastases of adenocarcinoma. The immunohistochemistry of the metastases led to the diagnosis of primary breast cancer. A negative FNA does not rule out the possibility of a malignant parotid tumor or metastasis, and a parotid lump should be presumed to be a secondary tumor until proven otherwise if the patient has a history of any distant primary cancer. Our patient case serves as a reminder that a new distant primary cancer might be the cause of a parotid lump.

Background: The continuous development of artificial intelligence (AI) and increasing rate of adoption by software startups calls for governance measures to be implemented at the design and development stages to help mitigate AI governance concerns. Most AI ethical design and development tools mainly rely on AI ethics principles as the primary governance and regulatory instrument for developing ethical AI that inform AI governance. However, AI ethics principles have been identified as insufficient for AI governance due to lack of information robustness, requiring the need for additional governance measures. Adaptive governance has been proposed to combine established governance practices with AI ethics principles for improved information and subsequent AI governance. Our study explores adaptive governance as a means to improve information robustness of AI ethical design and development tools. We combine information governance practices with AI ethics principles using ECCOLA, a tool for ethical AI software development at the early developmental stages. Aim: How can ECCOLA improve its robustness by adapting it with GARP® IG practices? Methods: We use ECCOLA as a case study and critically analyze its AI ethics principles with information governance practices of the Generally Accepted Recordkeeping principles (GARP®). Results: We found that ECCOLA's robustness can be improved by adapting it with Information governance practices of retention and disposal. Conclusions: We propose an extension of ECCOLA by a new governance theme and card, \# 21.

Extracellular vesicles (EVs) are secreted by most cell types under both physiological and pathological conditions and were proposed to be actively involved in intercellular communication. The mode of EVs action is dependent on their cargos composition. EVs play an important role in tumor initiation, recurrence, metastasis and therapeutic resistance. EVs marker proteins Alix and Tsg101 and cortactin are the binding partners of adaptor protein Ruk/CIN85. The present study aims to analyze the regulatory effects of EVs produced by 4T1 cells with overexpression (RukUp) or down-regulation (RukDown) of adaptor protein Ruk/CIN85 on proliferation rate, migration and invasion activity of parental 4T1 WT cells. EVs from conditioned medium of 4T1 RukUp or RukDown cells were isolated by differential centrifugation followed by further purification using Exo-spin™ kit (Cell Guidance Systems). The number and size of EVs were characterized by NTA (Malvern Panalytical NanoSight NM300) instrument. The content of marker proteins and Ruk/CIN85 in isolated EVs was analyzed by Western-blotting. The viability, migration and invasion activity of 4T1 WT cells were studied using MTT-test, scratch-test and Boyden chamber assay, respectively. It was demonstrated for the first time that adaptor protein Ruk/CIN85 is a constitutive component of EVs produced by 4T1 cells. It was also shown that EVs produced by 4T1 cells with different levels of Ruk/CIN85 expression are characterized by a specific profile of the content of its multiple molecular forms. It turned out that the ability of EVs to modulate the proliferative activity, motility and invasiveness of 4T1 WT cells was tightly correlated with the biological properties of 4T1 cells that produce EVs (highly aggressive 4T1 RukUp cells or weakly invasive 4T1 RukDown cells). Our data suggest that adaptor protein Ruk/CIN85 is not only a constitutive component of cargos composition of EVs produced by tumor cells but, depending on its content in EVs, plays an active role in the control of carcinogenesis.

Solar Energetic Particles (SEPs) are charged particles accelerated within the solar atmosphere or the interplanetary space by explosive phenomena such as solar flares or Coronal Mass Ejections (CMEs). Once injected into the interplanetary space, they can propagate towards Earth, causing space weather related phenomena. For their analysis, interplanetary in situ measurements of charged particles are key. The recently expanded spacecraft fleet in the heliosphere not only provides much-needed additional vantage points, but also increases the variety of missions and instruments for which data loading and processing tools are needed. This manuscript introduces a series of Python functions that will enable the scientific community to download, load, and visualize charged particle measurements of the current space missions that are especially relevant to particle research as time series or dynamic spectra. In addition, further analytical functionality is provided that allows the determination of SEP onset times as well as their inferred injection times. The full workflow, which is intended to be run within Jupyter Notebooks and can also be approachable for Python laymen, will be presented with scientific examples. All functions are written in Python, with the source code publicly available at GitHub under a permissive license. Where appropriate, available Python libraries are used, and their application is described.

Abstract Extracellular vesicles (EVs) represent a diverse group of small membrane-encapsulated particles involved in cell–cell communication, but the technologies to characterize EVs are still limited. Hypoxia is a typical condition in solid tumors, and cancer-derived EVs support tumor growth and invasion of tissues by tumor cells. We found that exposure of renal adenocarcinoma cells to hypoxia induced EV secretion and led to notable changes in the EV protein cargo in comparison to normoxia. Proteomics analysis showed overrepresentation of proteins involved in adhesion, such as integrins, in hypoxic EV samples. We further assessed the efficacy of time-gated Raman spectroscopy (TG-RS) and surface-enhanced time-gated Raman spectroscopy (TG-SERS) to characterize EVs. While the conventional continuous wave excitation Raman spectroscopy did not provide a notable signal, prominent signals were obtained with the TG-RS that were further enhanced in the TG-SERS. The Raman signal showed characteristic changes in the amide regions due to alteration in the chemical bonds of the EV proteins. The results illustrate that the TG-RS and the TG-SERS are promising label free technologies to study cellular impact of external stimuli, such as oxygen deficiency, on EV production, as well as differences arising from distinct EV purification protocols.

Abstract Background Chronic pulmonary embolism (CPE) is a life-threatening disease easily misdiagnosed on computed tomography. We investigated a three-dimensional convolutional neural network (CNN) algorithm for detecting hypoperfusion in CPE from computed tomography pulmonary angiography (CTPA). Methods Preoperative CTPA of 25 patients with CPE and 25 without pulmonary embolism were selected. We applied a 48%–12%–40% training-validation-testing split (12 positive and 12 negative CTPA volumes for training, 3 positives and 3 negatives for validation, 10 positives and 10 negatives for testing). The median number of axial images per CTPA was 335 (min–max, 111–570). Expert manual segmentations were used as training and testing targets. The CNN output was compared to a method in which a Hounsfield unit (HU) threshold was used to detect hypoperfusion. Receiver operating characteristic area under the curve (AUC) and Matthew correlation coefficient (MCC) were calculated with their 95% confidence interval (CI). Results The predicted segmentations of CNN showed AUC 0.87 (95% CI 0.82–0.91), those of HU-threshold method 0.79 (95% CI 0.74–0.84). The optimal global threshold values were CNN output probability ≥ 0.37 and ≤ -850 HU. Using these values, MCC was 0.46 (95% CI 0.29–0.59) for CNN and 0.35 (95% CI 0.18–0.48) for HU-threshold method (average difference in MCC in the bootstrap samples 0.11 (95% CI 0.05–0.16). A high CNN prediction probability was a strong predictor of CPE. Conclusions We proposed a deep learning method for detecting hypoperfusion in CPE from CTPA. This model may help evaluating disease extent and supporting treatment planning.

Spacecraft missions provide the unique opportunity to study the properties of collisionless shocks utilising in situ measurements. In the past years, several diagnostics have been developed to address key shock parameters using time series of magnetic field (and plasma) data collected by a single spacecraft crossing a shock front. A critical aspect of such diagnostics is the averaging process involved in the evaluation of upstream/downstream quantities. In this work, we discuss several of these techniques, with a particular focus on the shock obliquity (defined as the angle between the upstream magnetic field and the shock normal vector) estimation. We introduce a systematic variation of the upstream/downstream averaging windows, yielding to an ensemble of shock parameters, which is a useful tool to address the robustness of their estimation. This approach is first tested with a synthetic shock dataset compliant with the Rankine-Hugoniot jump conditions for a shock, including the presence of noise and disturbances. We then employ self-consistent, hybrid kinetic shock simulations to apply the diagnostics to virtual spacecraft crossing the shock front at various stages of its evolution, highlighting the role of shock-induced fluctuations in the parameters’ estimation. This approach has the strong advantage of retaining some important properties of collisionless shock (such as, for example, the shock front microstructure) while being able to set a known, nominal set of shock parameters. Finally, two recent observations of interplanetary shocks from the Solar Orbiter spacecraft are presented, to demonstrate the use of this systematic approach to real events of shock crossings. The approach is also tested on an interplanetary shock measured by the four spacecraft of the Magnetospheric Multiscale (MMS) mission. All the Python software developed and used for the diagnostics (SerPyShock) is made available for the public, including an example of parameter estimation for a shock wave recently observed in-situ by the Solar Orbiter spacecraft.

ABSTRACT Staphylococcus argenteus is a recently described member of the Staphylococcus aureus complex (SAC) and is associated with human disease. The frequency and intensity of infections caused by S. argenteus are similar to those of Staphylococcus aureus. S. argenteus can harbor antibiotic resistance genes and a variety of virulence factors analogous to methicillin-resistant S. aureus (MRSA). The aim of our study was to analyze a collection of isolates in the Dutch national MRSA surveillance from January 2008 until March 2021 that were nontypeable by multilocus variable-number tandem-repeat analysis (MLVA). Matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-ToF MS) was used for identifying the S. argenteus isolates, and whole-genome sequencing and SeqSphere were used to generate an in-house whole-genome multilocus sequence typing (wgMLST) scheme for typing the isolates. Furthermore, the presence of antibiotic resistance genes, replicons, and virulence genes was determined. Of 52,467 isolates submitted as MRSA from January 2008 until March 2021, 64 isolates (0.12%) were nontypeable with MLVA, and 54 of them were identified with mass spectrometry (MALDI-ToF MS) as S. argenteus. It appeared in retrospect that the first methicillin-resistant S. argenteus (MRSArg) was already submitted in 2008. An in-house-developed S. argenteus wgMLST scheme revealed that S. argenteus isolates clustered in 5 genomic groups which were characterized by distinct MLST types, resistomes, plasmid replicon families, and virulence factors. All but one isolate carried the staphylococcal chromosomal cassette mec (SCCmec) type IV harboring the methicillin resistance gene mecA and represent MRSArg. Most of the isolates with SCCmec subtype IVc(2B) had a trimethoprim resistance gene, dfrG, and harbored a blaZ-carrying plasmid, and most MRSArg isolates have the immune-modulating genes scn and sak. Nine of the 47 isolates carried enterotoxin-encoding genes seg, sei, sem, seo, and seu, which might be able to cause food poisoning. In some persons there was long-term persistence of MRSArg, and there were several genetically related MRSArg isolates in people living in close proximity, suggesting direct human-human transmission. IMPORTANCE We show that MRSArg has been circulating in the Netherlands since at least 2008. Although MRSArg is distinct from MRSA, it has a comparable population structure and carries similar resistance and virulence genes. The Dutch national MRSA surveillance has been expanded to include other methicillin-resistant members of the S. aureus complex, such as S. argenteus and Staphylococcus schweitzeri.

PyThea is a newly developed open-source Python software package that provides tools to reconstruct coronal mass ejections (CMEs) and shocks waves in three dimensions, using multi-spacecraft remote-sensing observations. In this article, we introduce PyThea to the scientific community and provide an overview of the main functionality of the core software package and the web application. This package has been fully built in Python, with extensive use of libraries available within this language ecosystem. PyThea package provides a web application that can be used to reconstruct CMEs and shock waves. The application automatically retrieves and processes remote-sensing observations, and visualizes the imaging data that can be used for the analysis. Thanks to PyThea, the three-dimensional reconstruction of CMEs and shock waves is an easy task, with final products ready for publication. The package provides three widely used geometrical models for the reconstruction of CMEs and shocks, namely, the graduated cylindrical shell (GCS) and an ellipsoid/spheroid model. It also provides tools to process the final fittings and calculate the kinematics. The final fitting products can also be exported and reused at any time. The source code of PyThea package can be found in GitHub and Zenodo under the GNU General Public License v3.0. In this article, we present details for PyThea‘s python package structure and its core functionality, and we show how this can be used to perform three-dimensional reconstruction of coronal mass ejections and shock waves.

Digital twin technology is the talking point of academia and industry. When defining a digital twin, new modeling paradigms and computational methods are needed. Developments in the Internet of Things and advanced simulation and modeling techniques have provided new strategies for building complex digital twins. The digital twin is a virtual entity representation of the physical entity, such as a product or a process. This virtual entity is a collection of computationally complex knowledge models that embeds all the information of the physical world. To that end, this article proposes a graph-based representation of the virtual entity. This graph-based representation provides a method to visualize the parameter and their interactions across different modeling domains. However, the virtual entity graph becomes inherently complex with multiple parameters for a complex multidimensional physical system. This research contributes to the body of knowledge with a novel graph-based model reduction method that simplifies the virtual entity analysis. The graph-based model reduction method uses graph structure preserving algorithms and Dempster–Shaffer Theory to provide the importance of the parameters in the virtual entity. The graph-based model reduction method is validated by benchmarking it against the random forest regressor method. The method is tested on a turbo compressor case study. In the future, a method such as graph-based model reduction needs to be integrated with digital twin frameworks to provide digital services by the twin efficiently.

Grasping and mouth movements have been proposed to be integrated anatomically, functionally and evolutionarily. In line with this, we have shown that there is a systematic interaction between particular speech units and grip performance. For example, when the task requires pronouncing a speech unit simultaneously with grasp response, the speech units [i] and [t] are associated with relatively rapid and accurate precision grip responses, while [ɑ] and [k] are associated with power grip responses. This study is aimed at complementing the picture about which vowels and consonants are associated with these grasp types. The study validated our view that the high-front vowels and the alveolar consonants are associated with precision grip responses, while low and high-back vowels as well as velar consonants or those whose articulation involves the lowering of the tongue body are associated with power grip responses. This paper also proposes that one reason why small/large concepts are associated with specific speech sounds in the sound-magnitude symbolism is because articulation of these sounds is programmed within the overlapping mechanisms of precision or power grasping.

Abstract Background The human sweat is a mixture of secretions from three types of glands: eccrine, apocrine, and sebaceous. Eccrine glands open directly on the skin surface and produce high amounts of water-based fluid in response to heat, emotion, and physical activity, whereas the other glands produce oily fluids and waxy sebum. While most body fluids have been shown to contain nucleic acids, both as ribonucleoprotein complexes and associated with extracellular vesicles (EVs), these have not been investigated in sweat. In this study we aimed to explore and characterize the nucleic acids associated with sweat particles. Results We used next generation sequencing (NGS) to characterize DNA and RNA in pooled and individual samples of EV-enriched sweat collected from volunteers performing rigorous exercise. In all sequenced samples, we identified DNA originating from all human chromosomes, but only the mitochondrial chromosome was highly represented with 100% coverage. Most of the DNA mapped to unannotated regions of the human genome with some regions highly represented in all samples. Approximately 5 % of the reads were found to map to other genomes: including bacteria (83%), archaea (3%), and virus (13%), identified bacteria species were consistent with those commonly colonizing the human upper body and arm skin. Small RNA-seq from EV-enriched pooled sweat RNA resulted in 74% of the trimmed reads mapped to the human genome, with 29% corresponding to unannotated regions. Over 70% of the RNA reads mapping to an annotated region were tRNA, while misc. RNA (18,5%), protein coding RNA (5%) and miRNA (1,85%) were much less represented. RNA-seq from individually processed EV-enriched sweat collection generally resulted in fewer percentage of reads mapping to the human genome (7–45%), with 50–60% of those reads mapping to unannotated region of the genome and 30–55% being tRNAs, and lower percentage of reads being rRNA, LincRNA, misc. RNA, and protein coding RNA. Conclusions Our data demonstrates that sweat, as all other body fluids, contains a wealth of nucleic acids, including DNA and RNA of human and microbial origin, opening a possibility to investigate sweat as a source for biomarkers for specific health parameters.

Phytophthora castaneae, an oomycete pathogen causing root and trunk rot of different tree species in Asia, was shown to harbor a rich diversity of novel viruses from different families. Four P. castaneae isolates collected from Chamaecyparis hodginsii in a semi-natural montane forest site in Vietnam were investigated for viral presence by traditional and next-generation sequencing (NGS) techniques, i.e., double-stranded RNA (dsRNA) extraction and high-throughput sequencing (HTS) of small RNAs (sRNAs) and total RNA. Genome organization, sequence similarity, and phylogenetic analyses indicated that the viruses were related to members of the order Bunyavirales and families Endornaviridae, Megabirnaviridae, Narnaviridae, Totiviridae, and the proposed family “Fusagraviridae.” The study describes six novel viruses: Phytophthora castaneae RNA virus 1–5 (PcaRV1-5) and Phytophthora castaneae negative-stranded RNA virus 1 (PcaNSRV1). All six viruses were detected by sRNA sequencing, which demonstrates an active RNA interference (RNAi) system targeting viruses in P. castaneae. To our knowledge, this is the first report of viruses in P. castaneae and the whole Phytophthora major Clade 5, as well as of the activity of an RNAi mechanism targeting viral genomes among Clade 5 species. PcaRV1 is the first megabirnavirus described in oomycetes and the genus Phytophthora.