Development of early life gut resistome and mobilome across gestational ages and microbiota-modifying treatments

Background: Gestational age (GA) and associated level of gastrointestinal tract maturation are major factors driving the initial gut microbiota composition in preterm infants. Besides, compared to term infants, premature infants often receive antibiotics to treat infections and probiotics to restore optimal gut microbiota. How GA, antibiotics, and probiotics modulate the microbiota\u27s core characteristics, gut resistome and mobilome, remains nascent. Methods: We analysed metagenomic data from a longitudinal observational study in six Norwegian neonatal intensive care units to describe the bacterial microbiota of infants of varying GA and receiving different treatments. The cohort consisted of probiotic-supplemented and antibiotic-exposed extremely preterm infants (n = 29), antibiotic-exposed very preterm (n = 25), antibiotic-unexposed very preterm (n = 8), and antibiotic-unexposed full-term (n = 10) infants. The stool samples were collected on days of life 7, 28, 120, and 365, and DNA extraction was followed by shotgun metagenome sequencing and bioinformatical analysis. Findings: The top predictors of microbiota maturation were hospitalisation length and GA. Probiotic administration rendered the gut microbiota and resistome of extremely preterm infants more alike to term infants on day 7 and ameliorated GA-driven loss of microbiota interconnectivity and stability. GA, hospitalisation, and both microbiota-modifying treatments (antibiotics and probiotics) contributed to an elevated carriage of mobile genetic elements in preterm infants compared to term controls. Finally, Escherichia coli was associated with the highest number of antibiotic-resistance genes, followed by Klebsiella pneumoniae and Klebsiella aerogenes. Interpretation: Prolonged hospitalisation, antibiotics, and probiotic intervention contribute to dynamic alterations in resistome and mobilome, gut microbiota characteristics relevant to infection risk. Funding: Odd-Berg Group, Northern Norway Regional Health Authority

A study of the side effects of Pandemrix influenza (H1N1) vaccine after whole-crew vaccination on board a Norwegian naval vessel

Background: The frigate His Norwegian Majesty’s ship (HNoMS) Fridtjof Nansen was participating in operations in the Gulf of Aden in support of the EU mission tasked with protecting vessels from the threat of piracy. The crew was therefore prioritized and given the first batch of Influenza A (H1N1) vaccine (Pandemrix®). Objectives: To investigate the type, frequency, and intensity of side effects after whole-crew vaccination with Pandemrix vaccine in healthy subjects in a controlled environment. Material and methods. A hundred and thirty-three members of the crew were vaccinated, and then they participated in the study. The side effects of the vaccination were evaluated through a survey. Results: Seventy-five per cent of the vaccinated sailors reported adverse reactions to the vaccine, with 9% not being able to perform their daily duties for one day. Muscle pain, headaches, malaise, and fatigue were the most frequent symptoms reported. Conclusions: The vaccination program using Pandemrix H1N1 vaccine resulted in a high rate of side effects, which were generally mild and resolved within a few days. No serious lasting side effects of the vaccination were reported or registered. The adverse effects of the vaccination did not affect the operational capacity of the vessel.publishedVersio

Kalveklassifisering og kalveslaktetilskudd for reinkalv

Klassifiseringssystemet EUROP ble innført for slakterein i 2015. Dette skulle stimulere reineierne til å levere slaktedyr med god kjøttfylde og med økt inntjening av den enkelte rein. Effektene av kalveslaktetilskuddet er vurdert, hvordan klassifiseringssystemet for kalv har fungert, og om kalveslaktetilskuddet bør knyttes til klassifiseringssystemet. Konklusjoner er: • Kalveslaktetilskuddet har fungert hensiktsmessig, men behovet er i dag endret • Tilskudd kan knyttes til kvalitet og motivere for langsiktig kvalitetsforbedring • Reindriftsfaglig grunnlag, forankring og tillit bør vektlegge

Regulation and quantification of cellular mitochondrial morphology and content

Mitochondria play a key role in signal transduction, redox homeostasis and cell survival, which extends far beyond their classical functioning in ATP production and energy metabolism. In living cells, mitochondrial content (“mitochondrial mass”) depends on the cell-controlled balance between mitochondrial biogenesis and degradation. These processes are intricately linked to changes in net mitochondrial morphology and spatiotemporal positioning (“mitochondrial dynamics”), which are governed by mitochondrial fusion, fission and motility. It is becoming increasingly clear that mitochondrial mass and dynamics, as well as its ultrastructure and volume, are mechanistically linked to mitochondrial function and the cell. This means that proper quantification of mitochondrial morphology and content is of prime importance in understanding mitochondrial and cellular physiology in health and disease. This review first presents how cellular mitochondrial content is regulated at the level of mitochondrial biogenesis, degradation and dynamics. Next we discuss how mitochondrial dynamics and content can be analyzed with a special emphasis on quantitative live-cell microscopy strategies.acceptedVersio

Fagarbeiderkompetanse. Kartlegging av dagens og fremtidens kompetansebehov i fagarbeiderrollen, i industri og bygg og anlegg.

publishedVersio

Electrosurgery and Temperature Increase in Tissue With a Passive Metal Implant

Importance: During monopolar electrosurgery in patients, current paths can be influenced by metal implants, which can cause unintentional tissue heating in proximity to implants. Guidelines concerning electrosurgery and active implants such as pacemakers or implantable cardioverter defibrillators have been published, but most describe interference between electrosurgery and the active implant rather than the risk of unintended tissue heating. Tissue heating in proximity to implants during electrosurgery may cause an increased risk of patient injury.Objective: To determine the temperature of tissue close to metal implants during electrosurgery in an in-vitro model.Design, Setting, and Participants: Thirty tissue samples (15 with a metal implant placed in center, 15 controls without implant) were placed in an in vitro measurement chamber. Electrosurgery was applied at 5–60 W with the active electrode at three defined distances from the implant while temperatures at four defined distances from the implant were measured using fiber-optic sensors.Main Outcomes and Measures: Tissue temperature increase at the four tissue sites was determined for all power levels and each of the electrode-to-implant distances. Based on a linear mixed effects model analysis, the primary outcomes were the difference in temperature increase between implant and control tissue, and the estimated temperature increase per watt per minute.Results: Tissues with an implant had higher temperature increases than controls at all power levels after 1 min of applied electrosurgery (mean difference of 0.16°C at 5 W, 0.50°C at 15 W, 1.11°C at 30 W, and 2.22°C at 60 W, all with p < 0.001). Temperature increase close to the implant was estimated to be 0.088°C/W/min (95% CI: 0.078–0.099°C/W/min; p < 0.001). Temperature could increase to above 43°C after 1 min of 60 W. Active electrode position had no significant effect on temperature increases for tissues with implant (p = 0.6).Conclusions and Relevance: The temperature of tissue close to a metal implant increases with passing electrosurgery current. There is a significant risk of high tissue temperature when long activation times or high power levels are used

WD40 Domain Divergence Is Important for Functional Differences between the Fission Yeast Tup11 and Tup12 Co-Repressor Proteins

We have previously demonstrated that subsets of Ssn6/Tup target genes have distinct requirements for the Schizosaccharomyces pombe homologs of the Tup1/Groucho/TLE co-repressor proteins, Tup11 and Tup12. The very high level of divergence in the histone interacting repression domains of the two proteins suggested that determinants distinguishing Tup11 and Tup12 might be located in this domain. Here we have combined phylogenetic and structural analysis as well as phenotypic characterization, under stress conditions that specifically require Tup12, to identify and characterize the domains involved in Tup12-specific action. The results indicate that divergence in the repression domain is not generally relevant for Tup12-specific function. Instead, we show that the more highly conserved C-terminal WD40 repeat domain of Tup12 is important for Tup12-specific function. Surface amino acid residues specific for the WD40 repeat domain of Tup12 proteins in different fission yeasts are clustered in blade 3 of the propeller-like structure that is characteristic of WD40 repeat domains. The Tup11 and Tup12 proteins in fission yeasts thus provide an excellent model system for studying the functional divergence of WD40 repeat domains

Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter

Objective. Proton therapy is highly sensitive to range uncertainties due to the nature of the dose deposition of charged particles. To ensure treatment quality, range verification methods can be used to verify that the individual spots in a pencil beam scanning treatment fraction match the treatment plan. This study introduces a novel metric for proton therapy quality control based on uncertainties in range verification of individual spots. Approach. We employ uncertainty-aware deep neural networks to predict the Bragg peak depth in an anthropomorphic phantom based on secondary charged particle detection in a silicon pixel telescope designed for proton computed tomography. The subsequently predicted Bragg peak positions, along with their uncertainties, are compared to the treatment plan, rejecting spots which are predicted to be outside the 95% confidence interval. The such-produced spot rejection rate presents a metric for the quality of the treatment fraction. Main results. The introduced spot rejection rate metric is shown to be well-defined for range predictors with well-calibrated uncertainties. Using this method, treatment errors in the form of lateral shifts can be detected down to 1 mm after around 1400 treated spots with spot intensities of 1 × 107 protons. The range verification model used in this metric predicts the Bragg peak depth to a mean absolute error of 1.107 ± 0.015 mm. Significance. Uncertainty-aware machine learning has potential applications in proton therapy quality control. This work presents the foundation for future developments in this area.publishedVersio

Uncertainty-aware spot rejection rate as quality metric for proton therapy using a digital tracking calorimeter

Objective. Proton therapy is highly sensitive to range uncertainties due to the nature of the dose deposition of charged particles. To ensure treatment quality, range verification methods can be used to verify that the individual spots in a pencil beam scanning treatment fraction match the treatment plan. This study introduces a novel metric for proton therapy quality control based on uncertainties in range verification of individual spots. Approach. We employ uncertainty-aware deep neural networks to predict the Bragg peak depth in an anthropomorphic phantom based on secondary charged particle detection in a silicon pixel telescope designed for proton computed tomography. The subsequently predicted Bragg peak positions, along with their uncertainties, are compared to the treatment plan, rejecting spots which are predicted to be outside the 95% confidence interval. The such-produced spot rejection rate presents a metric for the quality of the treatment fraction. Main results. The introduced spot rejection rate metric is shown to be well-defined for range predictors with well-calibrated uncertainties. Using this method, treatment errors in the form of lateral shifts can be detected down to 1 mm after around 1400 treated spots with spot intensities of 1 × 107 protons. The range verification model used in this metric predicts the Bragg peak depth to a mean absolute error of 1.107 ± 0.015 mm. Significance. Uncertainty-aware machine learning has potential applications in proton therapy quality control. This work presents the foundation for future developments in this area

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery