This review considers issues related to interpreting the mixed legacy of >300 papers published during the past three decades on possible genotoxic effects of exposure of human and animal tissues to radiofrequency electromagnetic fields (RF-EMF). The main paper reviews the evolution of consensus guidelines for genotoxicity testing and the increasing emphasis on systematic reviews for evaluation of scientific studies for use in health risk assessments. An Appendix considers some issues in assessing the bioeffects literature by examining a subset of genotoxicity publications that employed the comet assay. While most studies found no statistically significant effects of exposure, a significant minority of studies (chiefly, in vivo studies) reported statistically significant effects of exposure. The quality of the studies was highly variable; while several studies were meticulously done and documented, none of these studies were compliant with currently accepted guidelines such as those of the Organization for Economic Cooperation and Development (OECD). Evaluation of the studies using risk of bias (RoB) criteria showed that, in this sample of studies, higher quality studies were less likely to find statistically significant results than those of lower quality.
The authors conclude that statistical significance should be only one consideration in evaluation of bioeffects studies. Simply listing \'statistically\' significant effects identified using null hypothesis testing and the criterion p < 0.05 for statistical significance is misleading and uninformative in assessing health risks of exposure. A careful synthesis of evidence is needed, including assessment of study validity, biological significance of reported effects, and coherence of study results with those of other related studies.The authors recommend that all future RF genotoxicity studies intended for use in human health risk assessments and evaluations of the literature should be done in compliance with accepted quality guidelines, i.e. OECD or equivalent guidelines for genotoxicity screening studies and PRISMA or other accepted guideline for reviews of the literature. The positive studies in this group should be redone with tighter quality control to establish the reliability of the findings.

The Scientific Registry of Transplant Recipients (SRTR) held a consensus conference in 2012 that examined methods used by SRTR for constructing performance metrics and made recommendations on how to improve program-specific reports. That consensus conference provided 25 recommendations categorized as follows: statistical methods, risk adjustment, and outcomes and data. During the subsequent decade, SRTR has implemented most of these recommendations; these are described in this article along with plans for another consensus conference in 2022. With the present article, SRTR aims to create transparency in the field of transplant metrics and guide discussion in the planning of the next consensus conference in 2022. The new conference will revisit the previous topics and have a broader focus to improve the metrics and information that SRTR provides. Readers can provide feedback on topics to be discussed at the next consensus conference as early as possible, by emailing srtr@srtr.org with the subject line \"Task 5 Public Comment.\"

OBJECTIVE: The point-intercept method is one of the most commonly used approaches to measure species cover in ecosystems worldwide. In this approach, multiple points are sampled for presence/absence of a species, and the number of present points divided by the total number of sampled points provides an estimate of percent cover. Our purpose is to mathematically analyze the accuracy of the point-intercept approach and establish guidelines for its use.
METHODS: We developed formulas that analyze the point-intercept method and confirmed their effectiveness using simulations.
RESULTS: We find that a point-intercept spacing of at least 80% of the largest plant diameter provides the most reliable results. We present a user-friendly spreadsheet that calculates the number of intercepts needed for fieldwork, as well as the standard deviation, expected deviation, and confidence interval of the collected data.
CONCLUSIONS: We provide a variety of guidelines for establishing field protocols based on our results, including dealing with rare species and combining results for multiple species. Quadrat characteristics (intercept spacing, number of point intercepts) can now be easily calculated to guide research design prior to fieldwork; after fieldwork is complete, the accuracy of this technique can (and should) be reported in all future ecological studies in which it is used.

In the context of an increasing number of publications of trial data analysed by Bayesian methods, clinicians need support to better understand Bayesian statistical methods. The existing checklists are intended for people who already know these methods. We aimed to establish and validate a checklist that contains a group of items considered crucial in interpreting the results of a phase III RCT analysed with Bayesian methods.
A team of biostatisticians created a checklist of previously reported items and additional items identified from a literature review. Using three different articles in three rounds, the items were then validated by residents in anaesthesiology with no skills in statistics.
Based on an initial item list, three rounds led to a consensus checklist. Eleven items were considered important information to be specified for understanding the validity of the results. Of these, three were considered essential: specification of the prior, source of the prior (when prior is informative), and the effect size point estimate with its credible interval.
The checklist can help clinicians interpret the results of a phase III randomised clinical trial analysed by Bayesian methods, even clinicians with no particular knowledge of statistics, to ensure that the major elements of the statistical section are present and valid. Care should be taken in interpreting the results of a trial analysed by Bayesian methods that are not reported with these three essential items because the validity of the results cannot be established.

Introduction: The statistical quality of many trial-based economic evaluations is poor. When conducting trial-based economic evaluations, researchers often turn to national pharmacoeconomic guidelines for guidance. Therefore, this study reviewed which recommendations are currently given by national pharmacoeconomic guidelines on the statistical analysis of trial-based economic evaluations.Areas covered: 40 national pharmacoeconomic guidelines were identified. Data were extracted on the guidelines\' recommendations on how to deal with baseline imbalances, skewed costs, correlated costs and effects, clustering of data, longitudinal data, and missing data in trial-based economic evaluations. Four guidelines (10%) were found to include recommendations on how to deal with baseline imbalances, five (13%) on how to deal with skewed costs, and seven (18%) on how to deal with missing data. Recommendations were very general in nature and recommendations on dealing with correlated costs and effects, clustering of data, and longitudinal data were lacking.Expert opinion: Current national pharmacoeconomic guidelines provide little to no guidance on how to deal with the statistical challenges to trial-based economic evaluations. Since the use of suboptimal statistical methods may lead to biased results, and, therefore, possibly to a waste of scarce resources, national agencies are advised to include more statistical guidance in their pharmacoeconomic guidelines.

The aim of the study was to identify fungal spores, in particular plant pathogenic fungi, occurring in the air in selected mountain ranges. The results revealed not only the array of fungal species migrating with air currents from the Czech Republic and Slovakia but also how the season of the year affects the distribution of spores. Such studies may lay a foundation for future aeromycological monitoring, in accordance with the requirements for integrated plant protection. Aeromycological research was carried out between 2013 and 2016 at 3-month intervals in mountainous areas along the southern borders of Poland: the Bieszczady, the Pieniny, the Giant Mountains (Karkonosze) and the Babia Góra Massif. The research relied on impact method employing Air Ideal 3P sampler, which, by drawing in atmospheric air, also collects fungal spores. Regardless of altitudinal zonation, the changing weather conditions appeared to be the main reason for the variations in the number of the fungal spores under study in those years.