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The EFSA has updated the Guidance on risk assessment of the application of nanoscience and nanotechnologies in the food and feed chain, human and animal health. It covers the application areas within EFSA’s remit, including novel foods, food contact materials, food/feed additives and pesticides. The updated guidance, now Scientific Committee Guidance on nano risk assessment (SC Guidance on Nano‐RA), has taken account of relevant scientific studies that provide insights to physico‐chemical properties, exposure assessment and hazard characterisation of nanomaterials and areas of applicability. Together with the accompanying Guidance on Technical requirements for regulated food and feed product applications to establish the presence of small particles including nanoparticles (Guidance on Particle‐TR), the SC Guidance on Nano‐RA specifically elaborates on physico‐chemical characterisation, key parameters that should be measured, methods and techniques that can be used for characterisation of nanomaterials and their determination in complex matrices. The SC Guidance on Nano‐RA also details aspects relating to exposure assessment and hazard identification and characterisation. In particular, nanospecific considerations relating to in vitro/in vivo toxicological studies are discussed and a tiered framework for toxicological testing is outlined. Furthermore, in vitro degradation, toxicokinetics, genotoxicity, local and systemic toxicity as well as general issues relating to testing of nanomaterials are described. Depending on the initial tier results, additional studies may be needed to investigate reproductive and developmental toxicity, chronic toxicity and carcinogenicity, immunotoxicity and allergenicity, neurotoxicity, effects on gut microbiome and endocrine activity. The possible use of read‐across to fill data gaps as well as the potential use of integrated testing strategies and the knowledge of modes or mechanisms of action are also discussed. The Guidance proposes approaches to risk characterisation and uncertainty analysis. This publication is linked to the following EFSA Journal article: http://onlinelibrary.wiley.com/doi/10.2903/j.efsa.2021.6769/full This publication is linked to the following EFSA Supporting Publications articles: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2021.EN-6502/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2020.EN-1948/full

Background, aim and scope In 2005, a comprehensive comparison of life cycle impact assessment toxicity characterisation models was initiated by the United Nations Environment Program (UNEP)–Society for Environmental Toxicology and Chemistry (SETAC) Life Cycle Initiative, directly involving the model developers of CalTOX, IMPACT 2002, USES-LCA, BETR, EDIP, WATSON and EcoSense. In this paper, we describe this model comparison process and its results—in particular the scientific consensus model developed by the model developers. The main objectives of this effort were (1) to identify specific sources of differences between the models’ results and structure, (2) to detect the indispensable model components and (3) to build a scientific consensus model from them, representing recommended practice. Materials and methods A chemical test set of 45 organics covering a wide range of property combinations was selected for this purpose. All models used this set. In three workshops, the model comparison participants identified key fate, exposure and effect issues via comparison of the final characterisation factors and selected intermediate outputs for fate, human exposure and toxic effects for the test set applied to all models. Results Through this process, we were able to reduce inter-model variation from an initial range of up to 13 orders of magnitude down to no more than two orders of magnitude for any substance. This led to the development of USEtox, a scientific consensus model that contains only the most influential model elements. These were, for example, process formulations accounting for intermittent rain, defining a closed or open system environment or nesting an urban box in a continental box. Discussion The precision of the new characterisation factors (CFs) is within a factor of 100–1,000 for human health and 10–100 for freshwater ecotoxicity of all other models compared to 12 orders of magnitude variation between the CFs of each model, respectively. The achieved reduction of inter-model variability by up to 11 orders of magnitude is a significant improvement. Conclusions USEtox provides a parsimonious and transparent tool for human health and ecosystem CF estimates. Based on a referenced database, it has now been used to calculate CFs for several thousand substances and forms the basis of the recommendations from UNEP-SETAC’s Life Cycle Initiative regarding characterisation of toxic impacts in life cycle assessment. Recommendations and perspectives We provide both recommended and interim (not recommended and to be used with caution) characterisation factors for human health and freshwater ecotoxicity impacts. After a process of consensus building among stakeholders on a broad scale as well as several improvements regarding a wider and easier applicability of the model, USEtox will become available to practitioners for the calculation of further CFs.

The present study is based on a multidisciplinary approach carried out for the first time on Anacyclus pyrethrum var. pyrethrum and Anacyclus pyrethrum var. depressus, two varieties from the endemic and endangered medicinal species listed in the IUCN red list, Anacyclus pyrethrum (L.) Link. Therefore, morphological, phytochemical, and genetic characterisations were carried out in the present work. Morphological characterisation was established based on 23 qualitative and quantitative characters describing the vegetative and floral parts. The phytochemical compounds were determined by UHPLC. Genetic characterisation of extracted DNA was subjected to PCR using two sets of universal primers, rbcL a-f/rbcL a-R and rpocL1-2/rpocL1-4, followed by sequencing analysis using the Sanger method. The results revealed a significant difference between the two varieties studied. Furthermore, phytochemical analysis of the studied extracts revealed a quantitative and qualitative variation in the chemical profile, as well as the presence of interesting compounds, including new compounds that have never been reported in A. pyrethrum. The phylogenetic analysis of the DNA sequences indicated a similarity percentage of 91%. Based on the morphological characterisation and congruence with the phytochemical characterisation and molecular data, we can confirm that A. pyrethrum var. pyrethrum and A. pyrethrum var. depressus represent two different taxa.

The European Commission asked EFSA to update their 2006 opinion on ochratoxin A (OTA) in food. OTA is produced by fungi of the genus Aspergillus and Penicillium and found as a contaminant in various foods. OTA causes kidney toxicity in different animal species and kidney tumours in rodents. OTA is genotoxic both in vitro and in vivo; however, the mechanisms of genotoxicity are unclear. Direct and indirect genotoxic and non‐genotoxic modes of action might each contribute to tumour formation. Since recent studies have raised uncertainty regarding the mode of action for kidney carcinogenicity, it is inappropriate to establish a health‐based guidance value (HBGV) and a margin of exposure (MOE) approach was applied. For the characterisation of non‐neoplastic effects, a BMDL10 of 4.73 μg/kg body weight (bw) per day was calculated from kidney lesions observed in pigs. For characterisation of neoplastic effects, a BMDL10 of 14.5 μg/kg bw per day was calculated from kidney tumours seen in rats. The estimation of chronic dietary exposure resulted in mean and 95th percentile levels ranging from 0.6 to 17.8 and from 2.4 to 51.7 ng/kg bw per day, respectively. Median OTA exposures in breastfed infants ranged from 1.7 to 2.6 ng/kg bw per day, 95th percentile exposures from 5.6 to 8.5 ng/kg bw per day in average/high breast milk consuming infants, respectively. Comparison of exposures with the BMDL10 based on the non‐neoplastic endpoint resulted in MOEs of more than 200 in most consumer groups, indicating a low health concern with the exception of MOEs for high consumers in the younger age groups, indicating a possible health concern. When compared with the BMDL10 based on the neoplastic endpoint, MOEs were lower than 10,000 for almost all exposure scenarios, including breastfed infants. This would indicate a possible health concern if genotoxicity is direct. Uncertainty in this assessment is high and risk may be overestimated. This publication is linked to the following EFSA Supporting Publications article: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2020.EN-1845/full

Research on medicinal plants and extracts derived from them differs from studies performed with single compounds. Extracts obtained from plants, algae, fungi, lichens or animals pose some unique challenges: they are multicomponent mixtures of active, partially active and inactive substances, and the activity is often not exerted on a single target. Their composition varies depending on the method of preparation and the plant materials used. This complexity and variability impact the reproducibility and interpretation of pharmacological, toxicological and clinical research. This project develops best practice guidelines to ensure reproducibility and accurate interpretations of studies using medicinal plant extracts. The focus is on herbal extracts used in pharmacological, toxicological, and clinical/intervention research. Specifically, the consensus-based statement focuses on defining requirements for: 1) Describing the plant material/herbal substances, herbal extracts and herbal medicinal products used in these studies, and 2) Conducting and reporting the phytochemical analysis of the plant extracts used in these studies in a reproducible and transparent way. We developed the guidelines through the following process: 1) The distinction between the three main types of extracts (extract types A, B, and C), initially conceptualised by the lead author (MH), led the development of the project as such; 2) A survey among researchers of medicinal plants to gather global perspectives, opportunities, and overarching challenges faced in characterising medicinal plant extracts under different laboratory infrastructures. The survey responses were central to developing the guidelines and were reviewed by the core group; 3) A core group of 9 experts met monthly to develop the guidelines through a Delphi process; and. 4) The final draft guidelines, endorsed by the core group, were also distributed for feedback and approval to an extended advisory group of 20 experts, including many journal editors. The primary outcome is the \"Consensus statement on the Phytochemical Characterisation of Medicinal Plant extracts\" (ConPhyMP) which defines the best practice for reporting the starting plant materials and the chemical methods recommended for defining the chemical compositions of the plant extracts used in such studies. The checklist is intended to be an orientation for authors in medicinal plant research as well as peer reviewers and editors assessing such research for publication.

α-Amylases (E.C 3.2.1.1) hydrolyse starch into smaller moieties such as maltose and glucose by breaking α-1,4-glycosidic linkages. The application of α-amylases in various industries has made the large-scale productions of these enzymes crucial. Thermostable α-amylase that catalyses starch degradation at the temperatures higher than 50 °C is favourable in harsh industrial applications. Due to ease in genetic manipulation and bulk production, this enzyme is most preferably produced by microorganisms. Bacillus sp. and Escherichia coli are commonly used microbial expression hosts for α-amylases (30 to 205 kDa in molecular weight). These amylases can be purified using ultrafiltration, salt precipitation, dialysis, and column chromatography. Recently, affinity column chromatography has shown the most promising result where the recovery rate was 38 to 60% and purification up to 13.2-fold. Microbial thermostable α-amylases have the optimum temperature and pH ranging from 50 °C to 100 °C and 5.0 to 10.5, respectively. These enzymes have high specificity towards potato starch, wheat starch, amylose, and amylopectin. EDTA (1 mM) gave the highest inhibitory effect (79%), but Ca2+ (5 mM) was the most effective co-factor with 155%. This review provides insight regarding thermostable α-amylases obtained from microbial sources for industrial applications.

Pipelines are widely used for the transportation of hydrocarbon fluids over millions of miles all over the world. The structures of the pipelines are designed to withstand several environmental loading conditions to ensure safe and reliable distribution from point of production to the shore or distribution depot. However, leaks in pipeline networks are one of the major causes of innumerable losses in pipeline operators and nature. Incidents of pipeline failure can result in serious ecological disasters, human casualties and financial loss. In order to avoid such menace and maintain safe and reliable pipeline infrastructure, substantial research efforts have been devoted to implementing pipeline leak detection and localisation using different approaches. This paper discusses pipeline leakage detection technologies and summarises the state-of-the-art achievements. Different leakage detection and localisation in pipeline systems are reviewed and their strengths and weaknesses are highlighted. Comparative performance analysis is performed to provide a guide in determining which leak detection method is appropriate for particular operating settings. In addition, research gaps and open issues for development of reliable pipeline leakage detection systems are discussed.

To examine changes in proximal patellar tendon structure during the adolescent growth spurt in athletes. Prospective observational study. 173 adolescent athletes aged 11–15 years from specialised sporting programmes were recruited. Data collection occurred biannually for 2.5 years. Chronological age and maturity offset were calculated. Patellar tendons were scanned using ultrasound tissue characterisation, the proximal attachment was classified as having a hypoechoic area absent/present, and structure was quantified into four distinct echotypes (I–IV). Generalised additive models and generalised additive mixed modelling assessed associations between changes in echotype proportions and chronological age or maturity offset. 147 of 173 participants had normal tendon structure (i.e., no hypoechoic area) at baseline and across the study. In these tendons, a stronger linear association with maturation offset, but not chronological age, was observed for all echotypes suggesting a subtle improvement in tendon structure (p ≤ 0.01). Nine tendons (n = 8 participants) were hypoechoic at baseline and had a significant association with maturation offset and aligned tendon structure (echotype I; p ≤ 0.01) but not for disorganised tendon structure (echotypes III, IV; p = 0.6). Another 17 tendons (n = 15 participants) developed a hypoechoic area across the study. Proximal patellar tendon structure undergoes echotype changes during adolescence, which was linearly associated with maturity offset and not chronological age. Areas of disorganised patellar tendon structure in adolescents at baseline appeared unchanged despite continued exposure to high loads. Skeletal maturation appears a critical period in the development of a normal and abnormal, proximal patellar tendon attachment having implications for patellar tendinopathy prevention.

Processes of surface texture characterisation can be roughly divided into measurement issues and analysis of the results obtained. Both actions can be fraught with various errors, some of which can be analysed with frequency performance. In this paper, various types of surface topographies were studied, e.g., cylinder liners after the plateau-honing process, plateau-honed liners with additionally burnished dimples of various sizes (width and depth), turned, milled, ground, laser-textured, ceramic, composite and some general isotropic topographies, respectively. They were measured with a stylus or via optical (white light interferometry) methods. They were analysed with frequency-based methods, proposed in often applied measuring equipment, e.g., power spectral density, autocorrelation function and spectral analysis. All of the methods were supported by regular (commonly used) algorithms, or filters with (robust) Gaussian, median, spline or Fast Fourier Transform performance, respectively. The main purpose of the paper was to use regular techniques for the improvement of detection and reduction processes regarding the influence of high-frequency noise on the results of surface texture measurements. It was found that for selected types of surface textures, profile (2D) analysis gave more confidential results than areal (3D) characterisation. It was therefore suggested to detect and remove frequency-defined errors with a multi-threaded performance application. In the end, some guidance on how to use regular methods in the analysis of selected types of surface topographies following the reduction of both measurement (high-frequency noise) and data analysis errors was required.

We present here a perspective detailing the current state-of-the-art technologies for the characterisation of nanoparticles (NPs) in liquid suspension. We detail the technologies involved and assess their applications in the determination of NP size and concentration. We also investigate the parameters that can influence the results and put forward a cause and effect analysis of the principle factors influencing the measurement of NP size and concentration by NP tracking analysis and dynamic light scattering, to identify areas where uncertainties in the measurement can arise. Also included are technologies capable of characterising NPs in solution, whose measurements are not based on light scattering. It is hoped that the manuscript, with its detailed description of the methodologies involved, will assist scientists in selecting the appropriate technology for characterising their materials and enabling them to comply with regulatory agencies' demands for accurate and reliable NP size and concentration data.