We demonstrate the potential of the mobility signature approach through two applications that build on mobile-phone-based data from Finland. First, we use mobility signatures to show that the well-known radiation model is more accurate for mobility flows associated with larger Finnish cities, while the traditional gravity model appears a better fit for less populated areas. Second, we illustrate how the SARS-CoV-2 pandemic disrupted the mobility patterns in Finland in the spring of 2020. These two cases demonstrate the ability of the mobility signatures to quickly capture features of mobility flows that are harder to extract using more traditional methods.Understanding the patterns of human mobility between cities has various applications from transport engineering to spatial modeling of the spreading of contagious diseases. We adopt a city-centric, data-driven perspective to quantify such patterns and introduce  Collective human mobility patterns describe population movements between regions. To predict or quantify the flow volumes between regions, several classical theoretical models have been proposed by considering the impact of distances Zipf,  or interThere is, however, still a gap in quantifying the mobility characteristics of individual cities or regions. Here, a city-centric viewpoint that focuses on the mobility flows surrounding a city can be useful. As an example, mobility patterns to and from cities of different sizes and population density might respond differently to the SARS-CoV-2 pandemic.In this article, we introduce the city-centric mobility network similar to egocentric networks that are used in social network analysis . The results reveal that the mobility signatures of large municipalities are more compatible with the estimated mobility flows from the radiation model, while the signatures associated with the gravity model are a good estimation for mobility patterns for regions with medium or small populations. These results highlight a clear relation between mobility signatures and municipality size.Next, we focus on changes in the mobility signatures. To this end, we investigate the effects of the SARS-CoV-2 pandemic on the mobility patterns in Finland using the city-centric point of view. During the first phase of the SARS-CoV-2 outbreak, most countries across the globe established policies to control the spread of the disease by restricting human movements. Several studies  matrices. These matrices contain the number of trips between two geographical points or areas. There are several choices that need to be made when constructing OD matrices, including choosing spatial scales and period of observations . Regarding the temporal dimension, in the two applications below, we study networks aggregated over an entire year as well as the dynamics of monthly networks.Here, we want to focus on the features of individual municipalities and cities—how are they embedded in the country-wide mobility networks? To this end, we adopt the concept of egocentric networks from social-network studies to mobility networks. An egocentric network contains information on the direct social relationships of the ego  and her/his alters . Analogously, a city-centric network contains all mobility flows to/from a city; the country-wide mobility network can therefore be split into as many city-centric networks as there are cities. Note that in the following, we will use the terms city and city-centric network, even though the underlying data have been aggregated to the level of municipalities, as the vast majority of municipalities are technically cities.mobility signatures to characterize the city-centric networks  from the perspective of signature curves, i.e., how well the theoretical models capture the mobility characteristics of individual cities. Since population data are often updated annually, these mobility flows estimated from the two models generally reflect the mobility pattern of the corresponding year. We calculate the signatures of two classic mobility models by using the population data of 2019. Note that since in Telia data, flows below 20 trips per day have been excluded due to privacy requirements. In order to keep consistent with Telia data, in the theoretical models, we use the same threshold and omit flows of less than 20 trips between any two cities.Results for the mobility-derived and model-based signatures are displayed in The above hints that the radiation model could be more accurate for larger cities  for the two cities of Helsinki and Oulu . We use Combining the above results with the results shown in In this study, we introduce mobility signatures as a tool for quantifying the patterns of travel of individual cities in the overall mobility network. Similar to the signatures of egocentric networks in the social science literature, mobility signatures capture the relative importance of different destinations, and provide a way of measuring the heterogeneity of destinations.We apply this method to mobility networks constructed from mobile phone data for 310 Finnish municipalities. To assess to what extent the mobility signatures of cities can be explained by mobility patterns generated with the two commonly-used theoretical models, we measure the similarity of the mobility signatures extracted from empirical data and models. We find that the mobility signatures generated by the radiation model match better with the empirical signatures of larger cities, whereas the gravity model is more accurate for small and mid-sized cities.2). As the radiation model is based on the concept of intervening opportunities, sparsely populated regions may be outside its scope. On the other hand, the gravity model only depends on the distance between the two cities and their populations, which may explain why it works better for smaller cities.It would be interesting to see if the above result holds for other countries as well; it is worth noting that Finland's largest cities are fairly small compared to many countries, and that in Finland the population density is generally low and the distances large . The data are from February, March, April, and May in 2019 and 2020. The daily average number of trips between all pairs of locations is 3.4 million (2019) and 2.7 million (2020). For the two theoretical mobility models, we also use the population data for 2019 from Statistics Finland :mi is the number of residents who live in city i, mj is number of residents in city j and dij is the geographic distance between city i and city j. In the original formulation of Zipf (f(dij) = dij.ty Zipf, . This mo of Zipf , f(dij) i equals the empirical number of total outgoing trips ni+, and the attraction constraint is similar but regarding incoming trips:scikit-mobility  is the Shannon entropy of σi:k is the total number of destinations and Tij represents the number of outgoing trips from city i to city j. The JSD values are between 0 and 1, so that the closer the value is to zero, the more similar the pair of signatures is.The similarity of signatures of different cities and time intervals can be investigated using the Jensen-Shannon divergence (JSD). This measure is a generalized version of the Kullback-Leibler Divergence (KLD). Unlike the KLD, the JSD is symmetric, always well defined, and bounded Lin, . The JSDThe original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.JS, MA, and ZH: designed the research, analyzed the results, and wrote the manuscript. MA and ZH: processed the data and performed the analysis. All authors read, commented, and approved the final version of the manuscript.The study was part of the NetResilience consortium funded by the Strategic Research Council at the Academy of Finland (grant numbers 345188 and 345183).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Olea europaea L. subsp. europaea var. sylvestris) is the ancestor of cultivated olive (Olea europaea L. subsp. europaea var. europaea) and it is spread through the whole Mediterranean Basin, showing an overlapping distribution with cultivated olive trees. Climate change and new emerging diseases are expected to severely affect the cultivations of olive in the future. Oleaster presents a higher genetic variability compared to the cultivated olive and some wild trees were found adapted to particularly harsh conditions; therefore, the role of oleaster in the future of olive cultivation may be crucial. Despite the great potential, only recently the need to deeply characterize and adequately preserve the wild olive resources drew the attention of researchers. In this review, we summarized the most important morphological and genetic studies performed on oleaster trees collected in different countries of the Mediterranean Basin. Moreover, we reviewed the strategies introduced so far to preserve and manage the oleaster germplasm collections, giving a future perspective on their role in facing the future agricultural challenges posed by climatic changes and new emerging diseases.Oleaster ( Olea europaea L.) is one of the most iconic trees of Mediterranean Basin, with important implications from a social, economic, and ecological point of view [cuspidata is widely spread in Africa and Asia, subsp. laperrinei is present in the Sahara Desert, subsp. maroccana occurs mostly in Morocco, and subsp. guanchica and cerasiformis were found in the Canary Islands and Madeira, respectively [europaea is uniformly distributed across the whole Mediterranean Basin and is the only subspecies divided into two botanical varieties: cultivated olive (var. europaea) and wild olive or oleaster (var. sylvestris) [cerasiformis is a tetraploid and subsp. maroccana has a hexaploid cytotype [Olive  . Most ofcytotype .Cultivated olive originated from oleaster in northeastern Levant of Mediterranean Basin approximately 6000 years ago . The preWild and cultivated olive have overlapping distribution through the Mediterranean Basin even though the presence of oleaster is predominant in the central-western part of the Mediterranean area, where some old-growth forests were found . CultivaBeside genuine wild olives, which correspond to natural populations, there are the feral forms, secondary sexual derivatives originated from hybridization between cultivated trees and oleasters, as the two varieties are fully inter-fertile . Feral oXylella fastidiosa subsp. pauca) and olive decline caused by Pleurostomophora richardsiae, are generating significant concerns from an economic and ecological point of view [Xylella fastidiosa is of particular concern, as it has spread quickly in the last eight years, killing millions of olive trees, and is still expanding [Olive has adapted to grow in diverse climatic conditions with variable altitudes and different soils. Moreover, it can tolerate drought stress and different temperature regimes . Neverth of view ,17. QuicVerticillium dahliae [In this scenario, the availability of wild olive germplasm resources suitable for breeding programs and the preservation of this great source of genetic diversity is crucially important. The potential of wild olive as a source of resistance was widely proved with  dahliae ,19 and o dahliae ,21,22. M dahliae ,24,25,26One major concern about the use of wild olive in breeding programs is related to the supposed lower quality, in terms of fatty acids composition and phenolic compounds, of oil compared to extra virgin olive oil (EVOO) obtained from cultivated varieties. However, recent studies demonstrated that the use of wild olive in oil production does not have a negative impact on fatty acid composition, tocopherol, and phenolic composition, suggesting the suitability of oleaster in high-quality oil production ,28.In this review, we gave an outline of the most important morphological and genetic studies performed on different wild olive germplasm collections summarizing their principal findings and conclusions. Moreover, we performed a meta-analysis with the purpose of comparing the genetic differentiation found in different oleaster populations and their country of origin. Finally, we focused on the strategies introduced so far to preserve and manage the oleaster collections, giving a future perspective on how the wild olive genetic resources would be important to face the future agricultural challenges posed by climatic changes and new emerging diseases.Over the last 20 years, several studies focusing on the morphological and genetic characterization of oleaster populations were performed. The aims of these works were (1) to study the origin and domestication of cultivated olive; (2) to distinguish between genuine plants and feral forms; (3) to search out new sources of genetic variability for breeding programs; (4) to investigate the effects of human migration on olive domestication and selection; and (5) to describe the gene flow patterns existing in genuine wild populations. Morphological evaluation is the basis for olive characterization, but its dependence on plant development stages, the subjectivity of analysis, and the influence of environmental factors on its assessment have led to the progressive use of morphological descriptors in combination with molecular marker-based methods, which are fundamental in the genetic diversity assessment of large populations . europaea [Most morphological studies aimed to characterize oleaster with the purpose of exploring the diversity existing in isolated populations for the selection of individuals to include in specific conservation programs ,51,55 aneuropaea ,39,52. Teuropaea  assessedeuropaea ,60.europaea and other subspecies. For this reason, they included numerous samples collected in different countries of the Mediterranean Basin  have come to the same conclusions [In 2000, Besnard and Bervillé  performeclusions ,32.With the spreading of the use of SSR (simple sequence repeat) or microsatellite markers in olive genetic analysis, the number of studies aiming to dissect the molecular diversity existing in large natural populations of oleaster significantly increased. Most of them focused on large populations of oleaster located in specific areas of the Mediterranean Basin, with the main purposes of studying the genetic diversity within and among wild populations ,47, inveThe first large-scale molecular study of oleaster based on SSR markers was performed by Breton et al.  in 2006 O. europaea subsp. laperrinei) by microsatellite markers. The work confirmed the higher genetic diversity in oleaster compared with cultivars, as previously described [In 2013, Besnard et al.  performeescribed ,40,44, wDiez et al.  obtainedA large collection of oleaster samples from Spain was genetically analyzed by Beghè et al.  in 2017.cerasiformis and maroccana), making the comparison with diploid individuals a more straightforward process. Cytoplasmic markers allowed for the comparison of olive cultivar displacement in the Mediterranean area with the distribution of cytotypes in oleasters collected in different countries [Besides the use of nuclear molecular markers, cytoplasmic DNA polymorphism has been used, in particular, to investigate the phylogenetic relationships existing among subspecies and species of genus Olea. Indeed, the nucleotide variability of chloroplast and mitochondrial markers makes them extremely useful for evolutionary purposes. Moreover, cytoplasmic markers are extremely useful in the presence of polyploid species . The authors showed a high similarity of the chloroplast genome between var. sylvestris and var. europaea, demonstrating that a few differentiation events were present in the chloroplast DNA of subsp. europaea.The olive chloroplast DNA sequencing allowed for the development of new chloroplast molecular markers, which was useful to observe a geographic pattern of genetic differentiation that reflects the primary origins of cultivars in the Levant and highlighted a high genetic differentiation between perrinei ,62. Moreperrinei  performeThe whole genome sequencing of olive cultivar Farga in 2016 , oleasteUsing the whole genome resequencing of twelve olive samples, including one oleaster, Julca et al.  studied From all the studies about oleaster carried out so far, some key concepts have emerged and they are summarized in ST) is one of the most used. The FST was introduced by Wright [ST with expected and observed heterozygosity. A positive FST value indicates lower heterozygosity than expected due to inbreeding; on the contrary, a negative value means an excess of heterozygotes. A negative FST value may be due to the presence of factors contributing to increasing heterozygosity, such as the crossing with individuals belonging to other populations and a large number of widely dispersed individuals composing the population.Genetic studies about oleaster populations tried to dissect the variability existing within and between populations and described their genetic structure. Among the different genetic diversity indices, the fixation index  created an international network of germplasm banks as part of the RESGEN project. This network is composed of three international banks located in Córdoba (Spain), Marrakech (Morocco), and Izmir (Turkey), and 20 national banks  . The Worldwide Olive Germplasm Bank of Córdoba in Spain (WOGC—IFAPA) was established in 1970 and represented the first international attempt of the conservation and management of the olive germplasm. This is one of the largest olive germplasm collections, encompassing about 500 accessions from 21 countries . It inclA second Worldwide Olive Germplasm Bank was created at the INRA Research Station of Tassaoute, Marrakech  in 2003. This worldwide collection includes almost 560 accessions collected from 14 Mediterranean countries and it was genetically and morphologically characterized ,92. In 2sylvestris collected throughout the country, from farms, in situ, and ex situ collections [At a national level, an example of wild germplasm conservation is represented by the Gene Bank of the Agricultural University of Tirana, Albania, which preserves several accessions belonging to var. lections . Some oflections ,51,56. Alections . In addilections .Despite the efforts to include oleaster trees in these in situ and ex situ collections, great work is still needed to protect and preserve the huge genetic resource represented by the wild olive germplasm. The efforts made by the IOC, which has established a common guide to authenticate, sanitize, preserve and exchange plant material between banks, are essential to connect the ministries and the national supply agencies with the scientific communities. It is hoped that among the future goals of the IOC network there will also be greater attention to the identification and collection of wild olive trees through specific actions aimed at preserving them through appropriate conservation strategies.Recently, we have faced rapid climate change in most of the world’s regions; the Mediterranean Basin represents one of the most affected areas. Furthermore, these significant modifications are expected to progress in the next decades, severely affecting the cultivations of several crops, including olive ,15. In aeuropaea and sylvestris varieties. Moreover, it is notable that oleasters are spread all over the Mediterranean Basin and demonstrate an overlapping distribution with the cultivated olive [Oleaster constitutes a valuable source of genetic variability with huge potential for olive breeding, also thanks to the inter-fertile nature of the ed olive , making ed olive . Howevered olive , makes pIn the last years, the number of studies aiming to dissect the morphological and genetic variability existing in the populations of oleasters dispersed through the different Mediterranean countries has progressively grown. However, better knowledge and exploitation of wild olive is still needed. A thorough phenotyping, an accurate agronomical evaluation, and the application of high-throughput genotyping are fundamental to obtain an exhaustive comprehension of the variability existing in wild populations and identify the agronomic traits useful for future breeding programs. Extensive knowledge of large wild tree collection is also required to properly conserve and manage these resources in order to efficiently plan the exploration and collection of accessions, ensuring that the entire gene pool is adequately represented and minimizing redundancy. Several programs have been established all over the world aiming to conserve olive trees, but only a few of them included oleaster accessions. Some efforts have been made at the regional level; however, global and coordinated action is desirable to properly preserve the wealthy inheritance represented by these trees. The ex situ conservation is the easiest way to manage and protect olive genetic resources, although their conservation in their natural habitats is essential to maintain the genetic diversity existing in a wild population, which is continually adapting to local environmental conditions. The best approach would be to apply a combination of in situ and ex situ conservations, allowing the advantages of each method to complement each other. A single research center cannot efficiently conserve and preserve the numerous oleaster collections present in a specific territory; therefore, a wide international network is required to evaluate and catalog all the genetic resources of a certain area, ensuring the adoption of the best conservation strategy and management approach.For a long time, oleaster has been considered of lower agronomical value compared to the cultivated olive; however, the growing interest of researchers in its morphological, genetic, and chemical characterization has highlighted the huge genetic variability existing in populations of wild trees, their adaptability to harsh climatic conditions, such as dry and warm climates, and their suitability in the production of high-quality extra virgin olive oil, making these resources extremely precious when facing the challenges posed by climatic changes and new emerging olive diseases. The awareness of the great value represented by oleaster will boost the intention to valorize and protect this important and precious resource for the future of the olive species.


Germline genetic testing for patients with cancer can have important implications for treatment, preventive options, and for family members. In a mainstream genetic testing pathway, pre-test counseling is performed by non-genetic healthcare professionals, thereby making genetic testing more accessible to all patients who might benefit from it. These mainstream genetic testing pathways are being implemented in different hospitals around the world, and for different cancer types. It is important to evaluate how a mainstream genetic testing pathway can be made sustainable and if quality of genetic care is maintained. We show in this systematic review that it is feasible to incorporate a mainstream genetic testing pathway into routine cancer care while maintaining quality of care. A training procedure for non-genetic healthcare professionals and a close collaboration between genetics and other clinical departments are highly recommended to ensure sustainability.Background: Non-genetic healthcare professionals can provide pre-test counseling and order germline genetic tests themselves, which is called mainstream genetic testing. In this systematic review, we determined whether mainstream genetic testing was feasible in daily practice while maintaining quality of genetic care. Methods: PubMed, Embase, CINAHL, and PsychINFO were searched for articles describing mainstream genetic testing initiatives in cancer care. Results: Seventeen articles, reporting on 15 studies, met the inclusion criteria. Non-genetic healthcare professionals concluded that mainstream genetic testing was possible within the timeframe of a routine consultation. In 14 studies, non-genetic healthcare professionals completed some form of training about genetics. When referral was coordinated by a genetics team, the majority of patients carrying a pathogenic variant were seen for post-test counseling by genetic healthcare professionals. The number of days between cancer diagnosis and test result disclosure was always lower in the mainstream genetic testing pathway than in the standard genetic testing pathway . Conclusions: Mainstream genetic testing seems feasible in daily practice with no insurmountable barriers. A structured pathway with a training procedure is desirable, as well as a close collaboration between genetics and other clinical departments. BRCA gene [The use of germline genetic tests in cancer care is changing rapidly. Gene panel testing is increasingly being used instead of single gene testing, and the criteria for genetic testing have been broadened in several types of cancer ,2,3. In RCA gene ,5,6. TheThe development and implementation of a mainstream genetic testing pathway was first described by George et al. in 2016 in ovarian cancer patients, within the Mainstreaming Cancer Genetics program . SubsequThe systematic review of Scheinberg et al. studied the acceptability of mainstream genetic testing . They shWe performed a systematic review to assess the available literature on mainstream genetic testing in cancer care. The following research questions will be answered: (1) Is mainstream genetic testing in cancer patients feasible for NGHCPs in daily practice? and (2) Is the quality of genetic care maintained when patients undergo mainstream genetic testing?This review was conducted according to the guidelines established by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) report .Studies were eligible for inclusion if a mainstream genetic testing pathway in patients with cancer was evaluated. This pathway had to meet the following three criteria: (1) counseling and ordering of genetic testing was performed by a medical specialist, nurse specialist or nurse, not formally trained as a clinical geneticist or genetic counselor, (2) pre-test counseling was performed, and (3) genetic testing was performed with the primary aim of identifying pathogenic germline variants in patients with cancer.We considered the study of George et al. , publishOur search consisted of three main criteria: (1) cancer, (2) germline genetic testing, and (3) mainstream genetic testing. The full search was performed in collaboration with a library information specialist, and is shown in All identified studies were imported into Rayyan , a web tWe assessed the feasibility and quality of care of mainstream genetic testing. Whether the mainstream genetic testing initiatives were feasible for NGHCPs to implement in daily practice was assessed based on two outcomes: (1) the time investment for NGHCPs to discuss and order genetic testing and whether this was acceptable for them, and (2) barriers and facilitators for NGHCPs regarding mainstream genetic testing. We assessed quality of genetic care based on the following outcomes: (1) whether some form of training in genetics and genetic counseling was offered; (2) whether an informed consent procedure was described and how informed consent was documented; (3) whether patients carrying a pathogenic variant were invited for post-test counseling at a genetics department; (4) turnaround times for genetic testing ; and (5) whether genetic testing was performed according to national guidelines .Two authors (KB and MV) independently evaluated all selected articles using the Quality Improvement Minimum Quality Criteria Set (QI-MQCS), because mainstream genetic testing is considered to improve quality of care . The QI-We identified 537 articles through database searching. Five more articles were identified through reference and citation searching. After removing duplicates, another 439 articles were excluded based on title and abstract. The remaining 43 articles were assessed based on their full text, which led to the elimination of 26 more articles, resulting in 17 articles eligible for our analysis. See We included 17 papers that reported on 15 studies. These 15 studies included nine mainstream genetic testing pathways for patients with ovarian cancer, three for breast cancer, one for breast and ovarian cancer, one for endometrial cancer and one for prostate cancer. Of these 15 studies, 2 were performed in multiple countries and 13 in one country, mainly in the United Kingdom (8 out of 15 studies). All studies, except one , were coThe time investment for NGHCPs to discuss genetic testing with patients is shown in Barriers and facilitators of mainstream genetic testing for NGHCPs ,19,20,21In 14 out of 15 studies, a training program was offered to NGHCPs ,25,26,27All included studies described that patients provided informed consent before NGHCPs ordered a genetic test. In 10 out of the 15 studies, written informed consent was obtained ,24,25,26Six studies specified in their article or In three studies, all patients with a pathogenic variant were invited by the genetics department for post-test counseling by genetic healthcare professionals ,8,19,20.In 11 studies, NGHCPs needed to refer patients themselves if the results showed a pathogenic variant ,25,26,27The turnaround times are summarized in Three studies reported on the time between obtaining the test result with a pathogenic variant and referral to or attendance at a genetics department for post-test counseling ,21,23. FOnly two studies reported whether genetic tests were offered and/or performed according to current guidelines. In the study performed in Norway, it was assessed for all patients with breast cancer how many patients were eligible for genetic testing according to the Norwegian Breast Cancer Group (NBCG) criteria . Of all In the study by Gleeson et al., 93.1% of tested patients with ovarian cancer met national guidelines .The number of QI-MQCS criteria met per article varied between 6 and 13 out of 16, with an average of 8.9. Domains that were described sufficiently in nearly all articles were ‘Organizational motivation’ (16/16 met criteria), ‘Intervention description’ (16/16), ‘Implementation’ (15/16) and ‘Timing’ (15/16). The most insufficiently described domains were ‘Organizational characteristics’ (2/16 met criteria), ‘Penetration/Reach’ (3/16), ‘Adherence’ (4/16) and ‘Health outcomes’ (4/16).Based on the results of this systematic review, we conclude that it is feasible to incorporate mainstream genetic testing into daily practice because (1) the required time investment was acceptable for NGHCPs, despite the slightly increased workload, and (2) several facilitators and no insurmountable barriers were reported. We conclude that the quality of genetic care was maintained during mainstream genetic testing because (1) these mainstream genetic testing initiatives included genetics training for NGHCPs, (2) a comprehensive informed consent procedure was incorporated to ensure informed decision making, (3) most eligible patients received additional genetic counseling in case of a pathogenic variant, and (4) the turnaround times for genetic testing were comparable or shorter than in the standard genetic testing pathway. The fifth outcome measurement for quality of care, i.e., the proportion of patients receiving mainstream genetic testing that meet the eligibility criteria for testing, is understudied. Based on a combination of the results of our systemic review and those of the systemic review of Scheinberg et al. , we postIt is important that the time investment is reported in articles, because an acceptable time investment is a prerequisite for the implementation of a mainstream genetic testing pathway in daily practice. Compared to standard genetic counseling with an average time investment of 40 to 50 min ,30, the BRCA gene is identified. Patients should also be informed about the potential increased risk of breast, ovarian or prostate cancer for their family members [We identified two key discussion points for pre-test counseling that were described in six studies in this review, i.e., explanation of genes tested and cancer risks, and possible implications of a genetic test for the patients and their relatives ,18,20,26 members ,33.Shared decision making is essential in genetic pre-test counseling and a lack of time has shown to be an important barrier for shared decision making ,35,36. IWhether any important information that is needed to make an informed decision is left out by NGHCPs in mainstream genetic testing is not known and should be studied. It is also not known which topics are considered the most important by patients. The two most important barriers to mainstream genetic testing were inadequate knowledge by NGHCPs and the lack of time during appointments. The latter, however, was only described in one study, by the NGHCPs who had the least experience with mainstream genetic testing . When asAll these barriers were experienced in a research setting. Gleeson et al. determined which barriers were experienced by NGHCPs that would prevent them from continuing with mainstream genetic testing . These wFacilitators for mainstream genetic testing are the offer of a training program, FAQ forms, information sheets, and an approved clinical protocol. In this protocol, it should be stated clearly when NGHCPs can discuss and order genetic tests themselves and which actions are needed to obtain consent, order the genetic test, and when post-test counseling is needed by a genetic healthcare professional. For NGHCPs, it is important to learn about specific key topics that are needed to inform a patient before deciding whether or not to perform the genetic test. Training is therefore an important part of mainstream genetic testing initiatives, as all articles except one described that a training was used for NGHCPs prior to consulting patients ,25,26,27Several modules have been developed to train healthcare professionals in how to provide counseling regarding hereditary diseases ,41. ManyAlthough all studies reported that patients should receive post-test counseling by a genetic counselor in the case of a pathogenic variant, the actual referral and attendance rates varied between these studies. The most important difference between these studies seems to be whether or not these appointments for post-test counseling were directly coordinated by the genetics team. In the studies where patients were directly invited by the genetics team, almost all patients attended these appointments ,8,19,20.It is essential that all patients are offered post-test counseling by a member of the genetics team when a pathogenic variant is identified. Therefore, we recommend that appointments for post-test counseling be directly coordinated by the genetics team. Post-test counseling should be tailored to every patient, and attention should be paid to the practical implications and psychosocial impact of this test result. In addition, there is an important task in guiding patients to inform at-risk family members about cascade testing. Research has shown that even within the genetics departments the uptake of cascade testing is low, ranging from 21 to 44% . Given tBRCA gene have the highest response rates to PARP inhibitors [When the genetic test result has consequences for the treatment of cancer, it is important that turnaround times for genetic testing are minimized. For patients with ovarian cancer and prostate cancer for example, there is clear evidence that patients carrying a pathogenic variant in a hibitors ,46. The hibitors . A priorhibitors . Therefohibitors .Although most of the included studies reported on turnaround times, it is difficult to compare these results because different time points were used. The most frequently used turnaround time was the time between discussing a genetic test and disclosing the result to the patient, which ranged between 3 and 27 weeks. This illustrates that there are large differences between countries and laboratories. All studies that compared their mainstream genetic testing pathway with the standard pathway showed a reduction in turnaround time during the mainstream genetic testing period. However, it should be noted that most studies compared their turnaround times with periods before the implementation of their mainstream genetic testing pathway, and testing techniques might have been slower in those periods. Whether patients who received genetic testing fulfilled the criteria as stated in the national guidelines was only reported in two of the included studies ,18. As mThis review has some limitations. The results of our review may not easily be generalized to mainstream genetic testing in cancer settings other than ovarian cancer, as the majority (9 out of 15) of these initiatives available in the literature describe a mainstream genetic testing pathway for patients with ovarian cancer. The eligibility criteria for genetic testing in ovarian cancer are much more concise than they are for other types of cancer. Therefore, mainstream genetic testing in other types of cancer is more challenging. Another limitation is that there are no predefined and general definitions for feasibility and quality of care for genetic testing. Therefore, other articles might use other definitions to determine these outcomes. Lastly, the number of criteria met on the QI-MQCS critical appraisal tool per article was on average 8.9 out of 16. This means that, on average, only 56% of the domains were described sufficiently. The QI-MQCS manual did not always have strict guidance on whether a domain should be scored as ‘met’ or ‘not met’. Therefore, we might have been stricter than necessary, which could have resulted in lower scores. This review shows that there are multiple mainstream genetic testing initiatives which vary in their set-up. There are several elements that should be incorporated into mainstream genetic testing initiatives to increase the likelihood of successful implementation. These recommendations are summarized in Barriers regarding the local infrastructure were mentioned. It is important to explore in detail what these barriers are and to investigate this in different countries, due to differences in healthcare systems. In addition, the proportion of NGHCPs not willing to participate in mainstream genetic testing initiatives and their arguments for this should be studied further, as mainstream genetic testing initiatives can only be successful when a significant proportion of NGHCPs are participating. Mainstream genetic testing may become the new standard of care for specific patient populations, and therefore all NGHCP should be participating in the future. Currently, somatic genetic testing is increasingly used simultaneously with or as a prescreen for germline genetic testing . We thinSo far, mainstream genetic testing pathways have foremost been evaluated for patients with breast and ovarian cancer. For other types of cancers, there may be different barriers and facilitators that should be evaluated further. To determine whether mainstream genetic testing is an acceptable alternative for standard genetic testing, these outcomes should be evaluated more often in comparison to a control group receiving standard genetic testing. The available studies show that mainstream genetic testing for germline variants is feasible in the daily practice of NGHCPs treating patients with cancer. Mainstream genetic testing pathways present an acceptable increase in workload for NGHCPs, and the introduction almost always includes a training procedure. With the introduction of mainstream genetic testing pathways that include training for the NGHCP, the quality of care seems to be maintained. For feasibility as well as for quality of care, it is important that the genetics department has a pivotal role in the mainstream genetic testing pathways, especially in the coordination of post-test counseling of patients with a pathogenic germline variant.


Zonotrichia leucophrys) subspecies: Z. l. gambelii, Z. l. oriantha, and Z. l. pugetensis. Three types of genetic markers showed geographic distance between sampling sites, elevation, and ecosystem type are key factors contributing to population genetic structure. Microsatellite markers revealed white‐crowned sparrows do not group by subspecies, but instead indicated four groupings at a rangewide scale and two groupings based on coniferous and deciduous ecosystems at a local scale. Our analyses of morphological variation also revealed habitat differences; sparrows from deciduous ecosystems are larger than individuals from coniferous ecosystems based on principal component analyses. Habitat modeling showed isolation by distance was prevalent in describing genetic structure, but isolation by resistance also had a small but significant influence. Not only do these findings have implications concerning the accuracy of subspecies delineations, they also highlight the critical role of local factors such as habitat in shaping contemporary population genetic structure of species with high dispersal ability.Ecological, environmental, and geographic factors all influence genetic structure. Species with broad distributions are ideal systems because they cover a range of ecological and environmental conditions allowing us to test which components predict genetic structure. This study presents a novel, broad geographic approach using molecular markers, morphology, and habitat modeling to investigate rangewide and local barriers causing contemporary genetic differentiation within the geographical range of three white‐crowned sparrow ( Zonotrichia leucophrys). Microsatellite markers revealed that habitat influences genetic structure, as individuals found in coniferous ecosystems were genetically distinct from individuals found in deciduous habitats. Our results highlight the critical role of local ecosystem factors in shaping contemporary population genetic structure of species with high dispersal ability.In this study, we investigate the effect of rangewide and local barriers on contemporary genetic differentiation for western populations of white‐crowned sparrows ( It is a widespread North American passerine whose range spans multiple barrier types and is composed of five subspecies with different song dialects, habitat preferences, phenotype, and migration behaviors  how geographic distance and the rangewide barriers (such as the Rocky Mountains) influence genetic structure; (b) whether habitat and microclimate variation act as local barriers to gene flow; and (c) if suitable habitat corridors mediate gene flow for white‐crowned sparrows.We examined population genetic structure for three subspecies 22.1Z. l. pugetensis and Z. l. nuttalli populations breed on the Pacific Coast and (b) the Z. l. leucophrys –oriantha–gambelii populations breed to the east throughout North America . Birds were captured with mist‐nets using song playback over two breeding seasons  the a Figure . We sampa Figure  represenZ. l. pugetensis nestlings from four elevations in the Oregon Coast Range mountains  and Z‐linked Aldolase B6 gene (n = 54). For the CR, we designed a primer set: Finch Siskin CR L85 (5′‐GGCACATCCTTGTTTCAGGT‐3′) and H807 (5′‐CAGTGCCAAGTTTGMGACGA‐3′) to amplify a 576 bp sequence and used the primer set previously published by Cheviron and Brumfield (Genomic DNA was extracted from blood–ethanol mix or Longmire buffer (10 µl), tissue (~1 µg), or feather samples  using a modified Chelex procedure . The profile for amplification of CR was an initial cycle of 2 min at 94℃, 45 s at 50℃, and 1 min at 72℃; then 31 cycles of 30 s at 94℃, 45 s at 50℃, and 60 s at 72℃; and one final extension at 72℃ for 5 min followed by 4℃ for 20 s. The same conditions were used for AldoB except 2.5 mM MgCl2 and an annealing temperature of 62℃. Amplified DNA was sequenced at Genome Quebec . Chromatograms were checked and visually aligned using MEGA 6.0  were performed in a 25 µl reaction containing Green GoTaq® Flexi buffer (Promega), 0.2 mM dNTP, 2 mM MgCl2.32, 0.5 µM forward and reverse primer, 0.05 µM fluorescent M13 tag, 0.5 U GoTaq® Flexi DNA polymerase (Promega). The amplification profile consisted of a 2‐min denaturation at 94℃, 45 s at 50℃, and 1 min at 72℃; seven cycles of: 1 min at 94℃, 30 s at Tm1, and 45 s at 72℃; 31 cycles of; 30 s at 94℃, 30 s at Tm2, and 45 s at 72℃; and a final 5‐min elongation at 72℃. Annealing temperatures (Tm1/Tm2) differed for each primer set: Gf06, Pocc2, & VeCr05 (45/47), ZoleH02 (50/52), Gf01 & ZoleA2 (55/57), and Escu6, YW16, & ZoleC11 (60/62). For Escu6, the second step was decreased from 31 to 25 cycles. Products were visualized on a 6% acrylamide gel using a LI‐COR 4300 DNA Analyser . Three positive controls of known sizes were included for each locus to ensure consistent scoring. Genotyping data were scored by two separate observers to ensure consistent scoring, and any discrepancies were checked. A subset of samples (~24) was genotyped a second time to ensure consistent scores across gels.A subset of individuals was initially screened for amplification and variation with 26 passerine loci, 10 of which were designed for white‐crowned sparrows. In total, 12 loci produced PCR products, of which nine were polymorphic  for both AldoB6 and CR.Out of 54 birds used for AldoB6, 31 were male. Haplotypes from these males were reconstructed using PHASE in DnaSP v5   based on multilocus genotype data  and ΔK for each K  simulation to determine the number of genetic clusters  of 0.6. The optimal K was determined by choosing the K where the deviance information criterion (DIC) value began to plateau  between all populations was plotted against their geographic coordinates. A three‐dimensional PCoA graph was made using the Scatterplot3D package  and a Principal Component Analysis (PCA) were performed in R . Occurrences were limited to breeding season by filtering for data collected from mid‐April through August, and we restricted our occurrence data to points collected after 1980. We used environmental data from three separate sources: WorldClim Global Climate Dataset , MODIS‐based Global Land Cover dataset . The WorldClim Global Climate Dataset summarizes variables that measure of precipitation and temperature from 1970 to 2000, while the MODIS‐based Global Land Cover dataset summarizes land cover categorizing land cover into 16 distinct classifications.We constructed a species distribution model (SDM) to display potential dispersal routes of white‐crowned sparrows using least‐cost path (LCP) and least‐cost corridor (LCC) models. The SDM was made in ArcMap 10.1  using SDMtoolbox v1.1 Brown, . We obtaZ. l. gambelii, 285 for Z. l. oriantha, and 348 for Z. l. pugetensis. Next, the 19 environmental variables, land cover, and elevation layers were checked for autocorrelation and clipped to the extent of North America. Each subspecies' ecological niche was then modeled using Maxent v3.4  and the area under curve (AUC)  and calculated geographic distances between sites in GenAlEx 6.05  and isolation by resistance (IBR) on genetic differentiation. All Mantel and partial‐Mantel tests were conducted in GenoDive 3.04 , Z. l. pugetensis had the highest Hd for CR (Hd = 0.83), and both Z. l. pugetensis and Z. l. oriantha are similarly high for AldoB6  and northern (AB and BC) populations. One common haplotype was found in 32% of 85 sequences from eight populations, mostly northern populations  ranged from 0.43 (OK) to 0.75 (JAS and CO‐H), and expected heterozygosity (He) from 0.39 (OK) to 0.73 .Overall, we observed high population genetic structure and pairwise ns Table . GeneticF′ST values from all 15 populations ranged from 0 (JAS:RV) to 0.58 (BA:CO‐M), and 94 out of 105 (89.5%) comparisons were significant after FDR at the p < .05 level  and ΔK, K = 4 for microsatellite data from all 15 populations  were analyzed separately, the result was K = 2; however, no clear geographic pattern emerged  and RD, D‐G, and D‐T ecosites  JAS, RV, OK, and MK; (b) BA, BV, CNP, WT, LE, FTSJ, OR‐L, and OR‐H; and (c) CO‐L, CO‐M, and CO‐H. When running each of the three clusters independently, the DIC values indicated K = 2 within each group: (a) JAS, RV, OK, and (b) MK for the first group, (c) BA, BV, CNP, WT, LE, and FTSJ, and (d) OR for the second group, and (e) CO‐L, CO‐H, and (f) CO‐M for the third group  ecosite  from riparian deciduous (RD), disturbed‐gas (D‐G), and disturbed‐townsite (D‐T) ecosites . Unlike STRUCTURE, in TESS, BA clusters with the RD, D‐G, and D‐T group of ecosites not the AC ecosite.Using a spatial Bayesian clustering analysis in TESS Figure , the optp Figure . TESS unF′ST values showed the first two axes account for 34.5% and 23.6% of the variation with the third axis explaining 16.1% , precipitation of warmest quarter (10.6%), isothermality (8.2%) for Z. l. oriantha; and precipitation of coldest quarter (61.9%), precipitation seasonality (10.5%), precipitation of warmest quarter (10.5%), and elevation (8.2%) for Z. l. pugetensis (Supporting Information). The layers contributing to the SDM for Z. l. gambelii yielded an AUC value of 0.828, where 0.5 means the model fit is no better than random, and values close to 1 are a good fit. The layers contributing to the SDMs for Z. l. oriantha and Z. l. pugetensis yielded high AUC values of 0.996 and 0.995, respectively.The contemporary SDM for each subspecies closely followed their known distributions in North America Figures  and 5. TZ. l. gambelii showed dispersal routes with the lowest resistance were between mountain ranges in BC and through the Rockies in southwestern AB and southeastern BC. The southern Alberta Z. l. gambelii populations of LE, WT, CNP, and BV were connected via low elevation dispersal routes through the mountains to OK. Similarly, corridors connecting JAS to sites in BC had lower resistance than the corridors to other AB sites. Fort St. James and MK also had low resistance pathways connecting to OK, but not directly to each other. Temperature was the strongest contributor to the Z. l. gambelii SDM, yet dispersal patterns appeared to correspond to elevation. The Z. l. oriantha model showed low resistance north–south routes between CO, through the southern Alberta sites and extended up to MK along the lower elevation eastern foothills of the Rocky Mountains, a pattern that is corroborated by the importance of elevation as a contributor to this subspecies' SDM.The LCP and LCC for 3.4r = .24–.29, p ≤ .05). We were unable to separate the effects of these two processes, IBD and IBR, from each other . Among Z. l. oriantha and Z. l. gambelii populations, IBD and IBR were not significant. Additionally, IBD and IBR did not significantly affect genetic patterns among all Rocky Mountain populations.For our models examining all populations excluding the two Oregon populations, IBD and IBR were significant  and riparian deciduous (RD) ecosite types and individuals from disturbed ecosites grouped with the riparian deciduous individuals Figure . MorpholFicedula hypoleuca) resulting from competition , meadows of high sagebrush near the conifer timberline (Z. l. oriantha), and early seral coniferous forest (Z. l. pugetensis)  from the same area show unusual genetic patterns. Hybrids of mountain (Poecile gambeli) and black‐capped chickadees are more abundant in the FTSJ area ; formal analysis (lead); investigation (lead); methodology (lead); writing‐original draft (lead). Brendan Graham: Data curation ; writing‐review & editing . Ross R. Conover: Funding acquisition ; methodology ; writing‐original draft ; writing‐review & editing . James W. Rivers: Data curation ; funding acquisition ; methodology ; writing‐original draft ; writing‐review & editing . Theresa M. Burg: Conceptualization ; data curation ; funding acquisition ; investigation ; methodology ; project administration ; supervision ; writing‐original draft ; writing‐review & editing .Fig S1Click here for additional data file.Fig S1‐legendClick here for additional data file.


Advances in genetics and sequencing technologies are enabling the identification of more individuals with inherited cancer susceptibility who could benefit from tailored screening and prevention recommendations. While cancer family history information is used in primary care settings to identify unaffected patients who could benefit from a cancer genetics evaluation, this information is underutilized. System-level population health management strategies are needed to assist health care systems in identifying patients who may benefit from genetic services. In addition, because of the limited number of trained genetics specialists and increasing patient volume, the development of innovative and sustainable approaches to delivering cancer genetic services is essential.automated, patient-directed versus enhanced standard of care cancer genetics services delivery models. An algorithm-based system that utilizes structured cancer family history data available in the electronic health record (EHR) is used to identify unaffected patients who receive primary care at the study sites and meet current guidelines for cancer genetic testing. We are enrolling eligible patients at two healthcare systems  through outreach to a randomly selected sample of 2780 eligible patients in the two sites, with 1:1 randomization to the genetic services delivery arms within sites. Study outcomes are assessed through genetics clinic records, EHR, and two follow-up questionnaires at 4 weeks and 12 months after last genetic counseling contactpre-test genetic counseling.We are conducting a randomized controlled trial, entitled Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE), to address these needs. The trial is comparing uptake of genetic counseling, uptake of genetic testing, and patient adherence to management recommendations for BRIDGE is being conducted in two healthcare systems with different clinical structures and patient populations. Innovative aspects of the trial include a randomized comparison of a chatbot-based genetic services delivery model to standard of care, as well as identification of at-risk individuals through a sustainable EHR-based system. The findings from the BRIDGE trial will advance the state of the science in identification of unaffected patients with inherited cancer susceptibility and delivery of genetic services to those patients.NCT03985852. The trial was registered on June 6, 2019 at clinicaltrials.gov.BRIDGE is registered as The online version contains supplementary material available at 10.1186/s12913-021-06489-y. Hereditary cancer syndromes affect patients’ risks of many common, adult-onset cancers –5. PathoAdvances in genetics and sequencing technologies are allowing the identification of more individuals with an inherited cancer susceptibility who could benefit from tailored cancer screening and prevention recommendations. A growing number of genes have been associated with increased risks for breast, ovarian, colorectal, pancreas, and prostate cancers , 20–24. Efforts to identify individuals with inherited cancer susceptibility have generally focused on first testing patients who have had cancer with subsequent testing of their unaffected at-risk relatives once a PV is found –32. HoweNovel strategies are therefore needed to facilitate the use of family history information to identify unaffected individuals who may have inherited cancer susceptibility. Although some family history information is often collected in primary care settings, barriers to collecting or using this information in clinical practice include limited visit time; competing demands; reimbursement criteria; and providers’ training, knowledge and skills , 52–56. To address the need for a system-level population health management strategy, our team has developed an algorithm-based system to screen cancer family history information already available in the electronic health record (EHR) , and ideOnce unaffected individuals at risk for a hereditary cancer syndrome are identified, genetic services  need to be delivered. The number of trained genetic specialists is limited both in capacity and location, and more sustainable, and reimbursable, service delivery models are needed to accommodate an increasing patient volume –65. TherPrior research has compared different delivery models for cancer genetic services . A numbeFewer studies have explored supplementing genetic counselors with other models within the healthcare system , 76. As Use of automated conversational agents  may support a patient-directed genetic services delivery model for genetics education, decision making about genetic testing, and return of genetic test results. Chatbots have many advantages for patient education, including providing scripted education interactively, answering questions using natural language processing, chunking information into small segments that are easier to process, and allowing for choice in the amount of information received, consistent with adult learning recommendations –85. ThisIn examining the efficacy of genetic services delivery models, it is critical to explore how these effects may vary across population subgroups defined by factors such as race, ethnicity, and geographic location  to avoid worsening health disparities in access to care and health outcomes –100. PriIdentify unaffected patients receiving primary care who qualify for genetic risk assessment in two healthcare systems  using a clinical decision support algorithm to automatically evaluate family history of cancer through a population health management approach.Compare uptake of genetic counseling and testing for intervention  vs. enhanced standard of care  genetic services delivery models among unaffected patients who receive primary care at each site.Compare adherence to clinical care recommendations and patient cognitive and affective responses for the genetic services delivery models.To address the research needs of developing system-wide population health management strategies to identify unaffected patients at risk for inherited cancer syndromes and delivering cancer genetic services effectively across population subgroups, we are conducting the BRIDGE randomized controlled trial (RCT) with patients who receive primary care at two large healthcare systems. The BRIDGE trial has the following specific aims:The primary outcomes of the RCT will be uptake of genetic counseling, uptake of genetic testing, and, among those who receive genetic services, adherence to management recommendations from genetics providers. We hypothesize that uptake of genetic counseling and genetic testing will be equivalent between the two genetic services delivery models. We will also explore how race, ethnicity, and geographic location modify the effects of the cancer genetics services delivery models on these outcomes. In addition to the trial outcomes, we will assess implementation outcomes based on the RE-AIM  framework Table  116, 11.Table 1automated, patient-directed versus enhanced standard of care cancer genetics services delivery models. We are enrolling unaffected patients receiving primary care who are eligible for cancer genetic testing based on current National Comprehensive Cancer Network (NCCN) guidelines at two healthcare systems . We are enrolling patients through outreach to a randomly selected sample of 2780 patients . Eligible patients are identified using an open clinical decision support (CDS) infrastructure designed to extract cancer family history information available in the EHR. Identified patients are randomized 1:1 at each site prior to outreach to the study arms: automated, patient-directed intervention genetic services delivery model and enhanced standard of care control genetic services delivery model  to schedule a genetic counseling appointment. If the patient does not respond to the message, they receive a reminder patient portal message 1 week later and up to two follow-up telephone calls from a genetic counseling assistant (GCA). Procedures after this point follow standard workflow of the clinics. Interested patients are scheduled for a usual care pre-test genetic counseling appointment. These visits may be conducted by phone, telehealth, or in person at a designated time during clinic hours and with a certified genetic counselor following clinical standard of care. Patients who choose to proceed with genetic testing can give a sample of blood or saliva if seen in person. If counseled by telephone or telehealth, they are sent saliva collection kits which can be returned by mail; this service is offered by several commercial laboratories. All genetic test results are reviewed and returned by a genetic counselor either by phone or in person, based on patient preference. A copy of the results and letter with tailored cancer screening recommendations prepared by a genetic counselor are returned to the PCP. Patients who do not respond to initial outreach attempts are sent a final electronic message letting them know how to access genetic services in the future.In the control automated, patient-directed arm, patients are first sent an electronic message through the MyChart patient portal indicating that genetic services are recommended for them. The message includes a link with instructions to complete the pre-test education chat with the chatbot through the online platform. If the patient does not complete the chat, they receive a reminder patient portal message 1 week later and up to two follow-up telephone calls from a GCA. Following the completion of the pre-test education chat, a transcript is added into the patient’s EHR as an outreach encounter to document the education received. A GCA contacts each patient who completes the chat to review their decision about testing and complete a comprehensive family history. If the patient opts to proceed with testing, the GCA explains the genetic testing process and payment options and places the genetic testing order. The encounter is documented in the EHR using a clinic note template that is signed by a genetic counselor.In the intervention Patients in this arm who opt to have genetic testing are sent a saliva collection kit as described above. If the genetic sample is not returned to the lab within 30 days of order, the patient receives up to one reminder phone call and two electronic messages through the patient portal. All genetic test results are reviewed by a genetic counselor. Patients with negative results receive an electronic message in the patient portal which contains a link to a negative return of results chat with the chatbot. Transcripts of completed negative return of results chats are added to the patient’s EHR to document the encounter. Patients with PVs or variants of uncertain significance (VUS) have results returned by a genetic counselor via a telephone or telehealth visit. All patient test results  are uploaded to the patient portal along with a letter of tailored screening recommendations written by the genetic counselor. The patient’s PCP is also sent a copy of all documentation via Epic.Both chats in the automated, patient-directed arm  utilize the Invitae technical platform and chatbot interface and were scripted for the BRIDGE study by an interdisciplinary team of genetic counselors, genetic counseling assistants, communication scientists, and research staff. The chat content was developed through an iterative process of review of recorded genetic counseling encounters and feedback by certified genetic counselors in order to most closely represent key content delivered during in-person genetic counseling appointments. The pre-test education chat is introduced by a short video from a lead genetic counselor at each site and then provides educational content about heritability of cancer, genetic testing process, multi-gene panel tests, and possible genetic testing outcomes. The negative return of result chat informs the patient of their negative results and educates the patient about what these results mean for their long-term care. For both chats, patients move through a core set of information and then may request additional information on topics they choose. Both chats also provide the patient with the opportunity to ask questions in a free-text format. The platform utilizes a question bank so that the chatbot can respond automatically to most inquiries with a response pre-scripted by the research team, using natural language processing to determine the most appropriate response. If the system cannot match an answer to the patient’s question, the platform forwards the question to the GCA for follow up.Patients from both arms who decide not to test receive a letter summarizing their risks and recommendations based on the available personal and family history information. In addition, patients from both arms are offered the option to schedule follow-up appointments in the genetics clinics, and these contacts and appointments are tracked.All genetic testing is performed at a Clinical Laboratory Improvement Act (CLIA)-certified commercial laboratory and, for NYULH patients, New York State approved laboratory. Patients receive a pan-cancer, multigene panel test for cancer susceptibility genes that includes approximately 34–36 genes. As in clinical practice, the choice of laboratory and specific multigene panel test is based on the patient’s need, services provided, and the patient’s insurance/financial status. Testing is billed to insurance, or patients can opt to self pay. Patients who are uninsured or lack coverage for genetic testing can also be assisted in applying for aid through programs offered by the laboratories. The out-of-pocket cost of genetic testing is typically between $0–$250 based on prior clinical experience, with most paying less than $100.In order to collect data for the trial and implementation outcomes for participants who receive genetic counseling, we use a combination of questionnaires and abstraction of EHR data.Patients who complete pre-test counseling in either arm are asked to complete two follow-up questionnaires, with different versions for those who did and did not opt for genetic testing. The first follow-up questionnaire is administered about 4 weeks after the last genetic counseling contact and the second is administered 12 months after the last contact. As shown in Table Queries of structured data elements are used to abstract data from the EHR related to patients’ cancer family history and adherence to clinical management recommendations  at 12 months following genetic services. Data will be abstracted from the population health management registries at each site related to uptake of genetic counseling, uptake of genetic testing, and genetic test results.p < 0.05; SAS 9.4 and/or Stata 16.1 will be used for analysis.For the primary trial outcome analyses, we will first check randomization by comparing demographic characteristics between patients in the two arms using bivariate statistics . We will examine descriptive statistics, and will use chi-squared tests (or the nonparametric Fisher’s Exact test) with a two-sided 0.05 significance level for univariate comparison of proportions to examine the association between study arm and the primary outcomes . We will next build multilevel multivariable logistic regression models to examine the effect of study arm on the outcome controlling for clinic-level , provider-level , and patient-level  variables. Although the study design utilizes patient-level randomization and genetic counseling services are delivered centrally at both study sites, we will examine the intra-class correlation (ICC) by clinic and provider. If a significant ICC is observed, the regression models will be extended to include random effects for clinic or provider, and fit using software for generalized mixed models. Covariates will be included in models if significant in unadjusted analyses or if significantly different between arms. Using the multivariable regression models with interaction terms, we will explore whether the effects of study arm on uptake of genetic testing is modified by race/ethnicity or rurality. We will conduct both site-specific analyses and overall trial analyses. Statistical significance will be assessed as Sample size  is based on pilot tests of both arms at the two study sites in order to enroll approximately the same number of patients at each site. With outreach to 640 patients per arm at UHealth and 750 at NYULH, we will achieve 80% power to detect equivalence for the uptake of genetic counseling outcome in site-specific analysis. For this analysis, the margin of equivalence, given in terms of the difference, extends from − 0.08 to 0.17. The actual difference is 0.11, and the reference group proportion is 0.18. This sample size will be sufficient to examine the uptake of genetic testing outcome as well. For that outcome, 523 patients per arm at each site achieves 80% power to detect equivalence. The margin of equivalence, given in terms of the difference, extends from − 0.04 to 0.11. The actual difference is 0.05, and the reference group proportion is 0.14.The BRIDGE trial is designed to address the need to develop system-wide population health management strategies to deliver cancer genetic services to unaffected primary care patients. The primary outcomes of the trial will be uptake of genetic counseling, uptake of genetic testing, and, among those who receive genetic services, adherence to management recommendations from genetics providers. We hypothesize that uptake of genetic counseling and genetic testing will be equivalent for the automated, patient-directed genetic services delivery model delivered by a chatbot compared with the enhanced standard of care models. We will also explore whether race, ethnicity, and rurality modify the effects of the cancer genetics services delivery models on these outcomes.BRIDGE is addressing critical clinical needs of increasing hereditary cancer testing in appropriate populations and identifying individuals with inherited cancer susceptibility . InnovatAdditional file 1.


Plasmodium parasites, to investigate the interacting ecological and evolutionary mechanisms that put human and nonhuman primates at risk for infection. Plasmodium host switching from nonhuman primates to humans led to ancient introductions of the most common malaria-causing agents in humans today, and new parasite switching is a growing threat, especially in Asia and South America. Based on a wild host-Plasmodium occurrence database, we highlight geographic areas of concern and potential areas to target further sampling. We also discuss methodological developments that will facilitate clinical and field-based interventions to improve human and wildlife health based on this eco-evolutionary perspective.Parasites regularly switch into new host species, representing a disease burden and conservation risk to the hosts. The distribution of these parasites also gives insight into characteristics of ecological networks and genetic mechanisms of host-parasite interactions. Some parasites are shared across many species, whereas others tend to be restricted to hosts from a single species. Understanding the mechanisms producing this distribution of host specificity can enable more effective interventions and potentially identify genetic targets for vaccines or therapies. As ecological connections between human and local animal populations increase, the risk to human and wildlife health from novel parasites also increases. Which of these parasites will fizzle out and which have the potential to become widespread in humans? We consider the case of primate malarias, caused by  Animals host an incredible diversity of parasites, here defined as organisms that live in or on another organism (the host) at some cost to the host, including microparasites  and macroparasites (helminths and arthropods). Science is only just starting to understand this diversity of parasites, with the vast majority of parasites yet to be documented . Some paPlasmodium falciparum. Given the massive and global extent of anthropogenic change and its impacts on disease-carrying hosts  and adapt to humans, in some cases evolving to become specialists on humans , as seenng hosts , such evng hosts . Many ofng hosts . Given tng hosts .Giardia infecting many phylogenetically diverse species. In primates, for example, one study found that approximately 70% of known parasites are documented to infect more than one host , the number of individuals infected, and the Plasmodium species found. We followed the phylogenetic naming used by We build on the database published in Plasmodium species sampled from humans; that is, zoonotic malaria occurrences. We followed a similar approach, searching PubMed and Web of Science for studies published between January 2015 to August 2020 with the search terms ‘name of each Plasmodium species naturally found in primate populations’ followed by ‘human.’ For each publication, we recorded the location of infection when indicated (or the location where the blood sample was taken if unavailable), the number of individuals infected, and the Plasmodium species. We focus on this time period because molecular methods have dramatically changed the taxonomy and identification of zoonotic malaria, and we aim to avoid misclassification from early studies. Additionally, given the recent rise in sampling, we expect that this time period captures the vast majority of zoonoses.We next built a database of NHP Plasmodium parasites that regularly infect humans in natural settings, discussing the importance of transmission from NHPs to humans across timescales.Here, we review the origin and current status of the P. falciparum and P. vivax are responsible for approximately 95% of all malaria infections in human populations today  and South American monkeys (P. brasilianum)  . The dirilianum) . Howeverve trade . Relativte hosts , and mayP. ovale consists of two subspecies P. ovale curtisi and P. ovale wallikeri, and is mostly found in Malaysia and Africa . However, the presence of drug-resistant mutations can be used to predict the direction of transfer as human to ape. Using this evidence, the human P. falciparum has been found recurrently in primate populations living near humans , infecting only a few American NHPs .Consistent with the pattern of specialist  but see . The reaP. vivax relatives are generalists infecting all primate families considered here, substantial variation within lower taxonomic levels is observed; P. simium and P. vivax have only been found in a handful of South American monkey genera despite extensive sampling   . Anophelulations . The vecto occur .Multiple aspects of climate, including temperature, precipitation, and humidity, influence the life cycle of mosquito vectors and their geographic range, and thus can influence parasite sharing. For each developmental stage of the mosquitoes – from eggs to adults – the temperature is one of the most important factors that influence the duration of the passage from one stage to another; climatic change is likely to alter the distribution of the vector across latitudes and altitudes, and therefore the disease geography . BecauseP. knowlesi  occur in disturbed forest where human populations are more likely to be found , is a gene that encodes a surface glycoprotein. It is a classic example of adaptation in human evolution, with a single mutation producing the Duffy-null version of a surface glycoprotein that does not bind to P. vivax, preventing parasite invasion of host cells and most disease. Studies from multiple African populations have repeatedly found strong signatures of selection in human genomes at the DARC locus, likely because of its function in preventing P. vivax malaria , decreasing parasite invasion, and, in some cases, causing sickle cell disease and other hemoglobin disorders  and reticulocyte-binding proteins (RBPs) . In vitr deleted . The DBPon exist . Similaraffinity , perhapsP. simium support a role for DBPs and RBPs in parasite evolution to new hosts or host specificity (Despite the importance of DBPs and RBPs in parasite invasion of host red blood cells, less is known about the role of these pathways in shaping host specificity and risk of host switching. Early genomic resources that derive from passage through monkeys are missing common RBP genes founds in human field isolates , suggestcificity . Withoutcificity .Laverania parasites, and host switching of P. falciparum based on comparative genomic approaches (P. falciparum in humans. This is in contrast with the modern P. falciparum version of RH5, which is highly human-specific (P. knowlesi host switching (Multiple genes in red blood cell invasion pathways have also been implicated in the host specificity of proaches . Galawayspecific . Changeswitching .var and pir gene family variants, bind to host receptors, are involved in immune evasion and have been associated with disease severity (var genes have been identified in ape Laverania species, but their variation and impact on disease progression outside of humans is unclear, particularly because the corresponding ape immune response and genetic variation at immune genes is difficult to study in natural populations. Understanding the strain-specific immune responses and range of natural genetic variation is particularly important because var genes such as PfEMP1 have been proposed as vaccine targets, and expression of var genes has been shown to change in response to treatments (P. falciparum have had mixed success based on the genetic diversity of parasites (In addition to red blood cell invasion, immune response is central to host-parasite interactions and coevolution. These incredibly diverse genes, such as AMA1, MSP1, CSP, and the severity . var geneatments . Similararasites . Su et aP. vivax have been proposed as a barrier to an effective vaccine (P. vivax and P. falciparum, respectively (Further sampling to understand host and parasite ranges and natural genetic variation, population-genetic studies of adaptation, and experimental work on the mechanisms of host specificity will inform whether natural parasite variation is able to bind with common host genes necessary for invasion and, therefore, predict primate malarias with the highest potential for establishment of disease in other species . Host an vaccine , and DBPectively .Parasite transmission studies are often human-centric, focusing on animal-to-human transmission. Here, we emphasize a broader perspective that between-animal transmission also has direct medical and conservation impacts, and monitoring of NHP diseases should be a priority. This is particularly timely given recent conversations about long-term creation of reservoirs of SARS-CoV-2 in new animal populations, which could then serve as a new source for future evolution and spillover into humans.A broader perspective on the role of humans in disturbing environments, changing climates, and altering species interaction patterns will work synergistically with genetic and epidemiological research. Studies have increasingly demonstrated the importance of climatic and anthropogenic change on parasite and vector life cycles, but the ecology of the hosts is generally understudied. For example, mathematical modeling suggests that group size plays an important role in disease transmission dynamics and infection rates , though P. vivax versus P. simium or P. falciparum from other Laverania species – will be an important next step to stop human-NHP transmission pathways.Disease burdens, as well as resources, are not equally distributed between or within countries. Within-country capacity building is particularly important for monitoring primate and zoonotic malaria. It is especially important to provide that capacity building for new genomic technologies is facilitating noninvasive sampling and field-based sequencing. Improving the ability of rapid diagnostic tests or designing capture methods to differentiate between closely related parasite species from different hosts – such as Plasmodium genome sequences from around the world, particularly P. falciparum samples from Africa and Asia, and to a lesser extent P. vivax (Plasmodium species more suited to study recent population history (Plasmodium parasites undergo a complex life cycle through host and vector stages. Multiple steps involve processes expected to dramatically influence genetic variation, such as bottlenecks with transmission, rapid asexual population growth in primate hosts, and sexual recombination in vectors. The combination of these stages makes genetic variation difficult to predict or fit to common models, such as Wright–Fisher (FST scans, are difficult to interpret and may produce spurious results.Recent studies have produced hundreds to thousands of P. vivax . Robust  history . Despitet–Fisher . In turnA handful of studies have begun to address the challenge of understanding genetic variation by using simulation approaches, making substantial progress linking epidemiological and population-genetic models . These sP. falciparum that likely played a role in host switching from its putative ancestors in gorillas (P. vivax, however, is not amenable to long-term lab culture, so functional experiments have been limited and population-genetic data will play a central role (As genomic data for a wider variety of parasites becomes available, inference from population-genetic methods will instead be limited by our ecological and biological understanding of the systems. For example, more accurate estimates of mutation rates, the complexities of generation times, recombination rates, mosquito birth and death rates, and coinfection probability are needed to parameterize the models. An important next step will be to explore the phenotypic consequences and origins of the observed genetic variants hypothesized to play a role in host switching or transmission. To achieve this goal, functional tests are needed, together with population-genetic inference of adaptive versus neutral processes. Experimental studies have identified key pathways in gorillas . P. vivaral role . Combiniral role . Connect


The assessment of the genetic diversity of cultivated varieties is a very important element of breeding programs. This allows the determination of the level of genetic differentiation of cultivated varieties, their genetic distinctiveness, and is also of great importance in the selection of parental components for crossbreeding. The aim of the present study was to determine the level of genetic diversity of oat varieties currently grown in Central Europe based on two marker systems: ISSR and SCoT. The research conducted showed that both these types of markers were suitable for conducting analyses relating to the assessment of genetic diversity. The calculated coefficients showed that the analyzed cultivars were characterized by a high genetic similarity. However, the UPGMA and PCoA analyses clearly indicated the distinctiveness of the breeding programs conducted in Central European countries. The high genetic similarity of the analyzed forms allow us to conclude that it is necessary to expand the genetic pool of oat varieties. Numerous studies show that landraces may be the donor of genetic variation. The assessment of genetic diversity plays an important role in the characterization of breeding lines, cultivars, or species and is the basis for the selection of appropriate parental forms in the development of crossing. In the 20th century, more diverse and less productive landraces were increasingly replaced by modern elite cultivars. These cultivars were usually derived from crosses found among genetically related modern cultivars, which resulted in greater productivity but caused a significant reduction in genetic diversity ,2,3. ThiA. sativa L.) is one of the six most widely cultivated cereal species in the world. The world’s largest producers of oat, according to the FAO, are Russia; Canada; the United States; Australia; and European countries such as Poland, Finland, and Spain (FAOSTAT 2020). As in other cereals, in oats the high genetic similarity has also become a considerable problem for breeders [The common oat  are an efficient type of marker system that is multi-locus, dominant, reproducible, and highly polymorphic for genetic diversity studies. ISSR repeats are present mostly in the non-coding regions of chromosomes and specific stretches of non-active DNA sequences. The high occurrence of ISSR between normal coding genes and their presence within certain chromosomes as satellite bodies makes the ISSR unique and advantageous for use in DNA fingerprinting ,17. AnotEach marker type has its advantages and disadvantages; thus, the combination of several systems can be helpful for a better understanding of genetic diversity in analyzed species. In this study, we used the ISSR and SCoT markers to visualize the level of genetic diversity of oat varieties currently grown in Central Europe.Plant materials used in this study included 36 oat cultivars currently grown in Central Europe . GenomicThe ISSR amplification was carried out according to a modified method described by Zietkiewicz et al. . DNA ampThe results obtained were presented as a binary matrix in Excel. The presence or absence of a band was treated as a single feature and was assigned a value of 1 or 0, respectively.PIC) was calculated by applying the simplified formula [fi is the percentage of the i th amplified band present.The polymorphic information content  and the relative frequency of polymorphic products   were calRp) of the primers was calculated using the formula:Ib–band informativeness was calculated for each band scored by the primer individually.p is the proportion of occurrence of bands in the genotypes out of the total number of genotypes. The resolving power of the primers is a very useful parameter for the molecular diagnosis of any species from a mixed population [The resolving power (pulation .The genetic similarity index (SI) between all pairs of test forms was estimated according to Dice . PrincipOf the initially analyzed 30 ISSR (University of British Columbia–UBC) and 20 SCoT primers designed by Collard and Mackill , 8 and 5The resolving power of the ISSR primers ranged from 0.49 to 9.81, while that of the SCoT primers was in the range of 0.49 to 16.0. The average PIC value for the amplification products obtained from the ISSR primers was 0.168, ranging from 0.10 to 0.22. The average PIC value for the amplification products obtained from the SCoT primers was 0.154 and ranged from 0.08 to 0.21 .Based on the results obtained, a genetic distance matrix of 36 oat cultivars was created according to the Dice formula.For the ISSR, the similarity index values ranged from 0.814 to 0.949, with an average of 0.885. For the SCoT, the similarity index values ranged from 0.786 to 0.978, with an average of 0.891. Combined ISSR and SCoT results showed that the similarity index value ranged from 0.817 to 0.946, with an average of 0.887.A genetic similarity matrix was applied for the cluster analysis using the UPGMA method. Dendrograms were constructed on the basis of the similarity indexes obtained with the ISSR and SCoT markers and based on a combination of both methods. In all dendrograms, the analyzed varieties were clustered into two main groups of clusters. The first cluster was dominated by the Polish varieties, and the second by the Czech varieties. The groupings of the German varieties in the first or second group were ambiguous, depending on the marker system .The PCoA analysis largely reflected the clustering of varieties with the UPGMA method. Across the three plots, the Polish and the Czech cultivars formed separate cluster groups. PCoA analyses also allowed the distinguishing of the German varieties, which can be seen in particular in the plot obtained based on the combined ISSR and SCoT methods . The narrow genetic pool of cultivated varieties is a very serious problem for many cereals. Reduced genetic diversity can be seen particularly in studies comparing the genetic diversity of landraces and modern cultivars, indicating that it may be a result of carefully conducted breeding programs. Struss and Plieske  and ChenA. sativa varieties analyzed so far are characterized by a relatively narrow gene pool. This is especially shown for European varieties that are less diverse than those grown in North or South America [Data from the literature show that  America ,32.Genetic diversity studies are based mainly on DNA markers. Oat cultivars have been the subject of many different studies aimed at determining their level of genetic variation. These studies were based on various marker systems such as RAPD , AFLP 3,33,34, IIn the present study, the ISSR and SCoT markers were selected to evaluate the genetic similarity of chosen European oat varieties. Earlier studies have shown that ISSR markers are a good tool for assessing the level of genetic diversity of various cereal species ,50,51,52SCoT markers have been used numerous times to evaluate the genetic diversity of many cereals ,48,53,54As in previous studies on the assessment of the genetic diversity of oat cultivars, the present study showed that the analyzed varieties were characterized by a low level of genetic diversity and a narrow genetic pool. The mean values of similarity obtained for the ISSR and SCoT markers were 0.885 and 0.891 and were similar to those obtained by Paczos-Grzeda , based oIn the current research, based on the Dice genetic similarity index matrix, UPGMA cluster analysis and PCoA analysis were performed. The topology of the dendrograms was consistent with the arrangement of objects in the PCoA plots. Based on the analysis, it can be concluded that the grouping of varieties is consistent with their place of origin. Similar results were obtained by Paczos-Grzęda et al. , who shoIn summary, it can be concluded that the oat varieties currently grown in Central Europe are still characterized by a very low level of polymorphism. Both the ISSR and SCoT markers indicated a very narrow genetic pool; however, there are differences between the breeding programs carried out in individual countries. The conducted research indicates the need to expand the genetic variability of cultivated varieties. An excellent source may be, for example, local varieties, which are characterized by a very high level of genetic diversity compared to modern varieties ,34.