Past, present and future of chamois science

The chamois Rupicapra spp. is the most abundant mountain ungulate of Europe and the Near East, where it occurs as two spe- cies, the northern chamois R. rupicapra and the southern chamois R. pyrenaica. Here, we provide a state-of-the-art overview of research trends and the most challenging issues in chamois research and conservation, focusing on taxonomy and systematics, genetics, life history, ecology and behavior, physiology and disease, management and conservation. Research on Rupicapra has a longstanding history and has contributed substantially to the biological and ecological knowledge of mountain ungulates. Although the number of publications on this genus has markedly increased over the past two decades, major differences persist with respect to knowledge of species and subspecies, with research mostly focusing on the Alpine chamois R. r. rupicapra and, to a lesser extent, the Pyrenean chamois R. p. pyrenaica. In addition, a scarcity of replicate studies of populations of different subspecies and/or geographic areas limits the advancement of chamois science. Since environmental heterogeneity impacts behavioral, physiological and life history traits, understanding the underlying processes would be of great value from both an evolutionary and conservation/management standpoint, especially in the light of ongoing climatic change. Substantial contri- butions to this challenge may derive from a quantitative assessment of reproductive success, investigation of fine-scale foraging patterns, and a mechanistic understanding of disease outbreak and resilience. For improving conservation status, resolving taxonomic disputes, identifying subspecies hybridization, assessing the impact of hunting and establishing reliable methods of abundance estimation are of primary concern. Despite being one of the most well-known mountain ungulates, substantial field efforts to collect paleontological, behavioral, ecological, morphological, physiological and genetic data on different popu- lations and subspecies are still needed to ensure a successful future for chamois research and conservation

20-Year Risks of Breast-Cancer Recurrence after Stopping Endocrine Therapy at 5 Years

The administration of endocrine therapy for 5 years substantially reduces recurrence rates during and after treatment in women with early-stage, estrogen-receptor (ER)-positive breast cancer. Extending such therapy beyond 5 years offers further protection but has additional side effects. Obtaining data on the absolute risk of subsequent distant recurrence if therapy stops at 5 years could help determine whether to extend treatment

Experimental Investigation on Steam Condensation in the Presence of Air and Helium: Forced Convection Conditions

This paper discusses the results obtained from recent experimental investigations devoted to the study of steam condensation in the presence of air and a light noncondensable gas. The experiments are intended to provide data for the validation of engineering models and CFD codes. The original experimental data herein discussed focus on forced convection turbulent boundary layer conditions and involve atmospheric pressure, different conditions for mixture velocity (from 1.5 to 3.5 m/s), mixture composition (form 0 to 75 per cent of the light species in the overall amount of noncondensable gases) and two nominal electrical power supply of the steam generator. The experimental data are qualified against correlations based on the heat and mass transfer analogy and to the predictions obtained by an in house condensation model implemented in a commercial CFD code

AP1000 Recovery Improvement After ADS Inadvertent Actuation

The AP1000® advanced Pressurized Water Reactor (PWR) is designed and developed by Westinghouse Electric Company. The AP1000® safety approach and design are such that the plant is capable to mitigate all the Design Basis Accidents (DBAs) relying only on passive safety systems with no AC power and no or very limited operator action. In addition to the passive features, the active systems within the AP1000 design are classified as non-safety related systems, coherently with the fact that they are not needed in an accident scenario and that the plant is surely safe also postulating their failure following a DBA. The high standard against which these active systems are designed and the margin in the design, make the systems realistically available following a DBA and, hence, they could be used to mitigate the accident and improve plant recovery after the accident. A demonstration on how the Normal Residual Heat Removal System (RNS), an active non-safety related system, could be used to mitigate a DBA is given in this paper. The selected accident is the inadvertent actuation of the Automatic Depressurization System (ADS) initially occurring with the plant operating at full power. Relap5 is a computer code well adapted to analyzing this event. Relap5 simulations of the accident, performed on a suitable detailed model of the AP1000® developed in Ansaldo Nucleare S.p.A., demonstrate that RNS can actually be used to reduce the impact of this accident on the containment, hence improving plant recovery after the accident

Conditions determining PCR success in otter landscape genetics

Non-invasive sampling for genetic analysis using DNA from feces is a useful technique to monitor animal populations. But despite being a very promising tool, it still has some limitations and can give some problems such as low success rates of genotyped samples, contamination concerns and high microsatellite genotyping error rates. To optimize success, it is important to follow specific steps, including a stringent sample selection in the field, proper storage conditions, and choice of the optimal DNA extraction method for the study species. Furthermore, the PCR success rate could potentially be influenced by factors prior to collection, such as temperature and the diet of the species, as well as by sample storage time. Here, we investigated the effect of temperature at time of collection, average maximum temperature one week prior to collection and storage time on the amplification success rate of microsatellite DNA extracted from XX fecal samples of the Eurasian otter (Lutra lutra) in the Netherlands. To do this, we considered two cases: firstly, we performed a logistic regression to assess whether temperature at time of collection and/or storage time could be used to predict the genotyping success rate for one microsatellite locus, that is used as a primary selection tool for sample quality. Secondly, we considered PCR success rate as the number of successfully scored loci out of the total 13 loci used in the landscape genetic study of Dutch otters and assessed the effect of temperature at time of collection, average maximum temperatures one week prior to collection and storage time. Results showed that when considering one locus only, the amplification success rate was not influenced by temperature. However, when considering all the loci temperature at time of collection and temperature one week prior positively influenced the PCR success rate, meaning that as the temperature raised, the success rate increased. This result was contrasting most of the literature, indeed, as it would be expected, high temperatures should cause a more rapid degradation of DNA caused by higher activity of hydrolytic enzymes in feces. Probably there were outside factors (e.g. the otters\u2019 diet) that we did not control and that were confounded with temperature requiring the need for further investigation. Storage time had no effect on DNA amplification success rate in any of our tests. Our results suggest that DNA amplification success rate is influenced by many factors. Before starting a non-invasive study, it is fundamental to take into account several factors and to study to what extent each factor influences the amplification success in order to maximize the DNA amplification success rate and to reduce genotyping error rates

Radiomics and predictive models applied to head and neck radiotherapy: an over-view of ongoing trials

Radiomics and predictive models applied to head and neck radiotherapy: an overview of ongoing trials Radiomica e modelli predittivi applicati alla radioterapia dei tumori testa-collo: una overview degli studi ongoing Aims: In radiation oncology practice, comprehensive information on tumor genomic profile and tumor characteristics extractable by imaging can improve treatment planning and clinical response evaluation. Current studies on radiomics and predictive models of radiation-induced side effects (RISE) and/or tumor response will provide more informative results. In this paper we report a short overview of current modeling studies in patients subjected to radiotherapy (RT) for head and neck cancers (HNC) with the main scope to provide a preliminary explorative analysis on these topics. Methods: In April 2019 we performed an advanced search on clinicaltrials.gov website using the following keywords and strategy: “Head and Neck Radiotherapy” AND “Predictive models OR Mathematical models OR Radiomic features”. Studies in the following recruitment status: Suspended, Withdrawn and Unknown Status, as well as trials enrolling pediatric patients, were excluded. Both studies assessing RISE and tumor response have been selected and analyzed. We extracted data regarding study type, patients’ number, recruitment status, model assessment, inclusion criteria, primary and secondary outcome measures. Results: Our search provided 3 studies (Table 1). All trials were recruiting at the time of our search. A total of 2460 patients were expected. No definitive results were available. The NCT03294122 and NCT02489084 studies are assessing models to predict RISE in HNC, regardless of the primary tumor site. In this setting, we observed an emerging interest on the role of the microenvironment (e.g. microbiota, inflammatory markers), as well as on tissue features extracted by radiomic analyses and DNA profiles. Another study (NCT03656133) is specifically assessing tumor response of p16+ or HPV+ squamous cell oropharynx carcinoma by determining whether a mathematical model based on the individual patient “proliferation saturation index” is able to predict rapid tumor response and support the decision of personalized RT fractionation. Conclusion: Comprehensive database of clinical, genetic, biological, imaging, dosimetric data are needed to match the collected information. The management of big data to aid the decision-making in clinical practice requires a multidisciplinary approach and experts’ support. Tolerance and effectiveness of RT for HNC could be improved by using these innovative approaches. Definitive results and further validations of the proposed models are necessary