Indri indri) are the only singing lemurs and emit songs whose most distinctive portions are “descending phrases” consisting of 2-5 units. We examined how the structure of the indris’ phrases varied with genetic relatedness among individuals. We tested whether the acoustic structure could provide conspecifics with information about individual identity and group membership. When analyzing phrase dissimilarity and genetic distance of both sexes, we found significant results for males but not for females. We found that similarity of male song-phrases correlates with kin in both time and frequency parameters, while, for females, this information is encoded only in the frequency of a single type. Song phrases have consistent individual-specific features, but we did not find any potential for advertising group membership. We emphasize the fact that genetic and social factors may play a role in the acoustic plasticity of female indris. Altogether, these findings open a new perspective for future research on the possibility of vocal production learning in these primates.The increasing interest in the evolution of human language has led several fields of research to focus on primate vocal communication. The ‘singing primates’, which produce elaborated and complex sequences of vocalizations, are of particular interest for this topic. Indris ( While many species make a conspicuous use of vocalizations, a limited number of taxa communicate using a sequence of vocal emissions, usually termed songs2. A song is a combination of different components that can be described hierarchically. Individual sounds are referred to as ‘units’, ‘elements’ or ‘notes’. One or more units that occur together can be called song ‘syllables’, and a sequence of one or more syllables is described as either a ‘phrase’ or ‘motif’. Since Darwin, scholars have been interested in understanding whether the complexity of singing is genetically determined, impacted by social experience, or the result of a learning process4. The processes leading to song diversity have been widely investigated in birds. Endogenous and exogenous factors modulate the interplay between genetic characteristics, social experience, and learning5. For instance, early findings on song development in the zebra finches (Taeniogypta guttata) suggested that, while male birds develop their song during a sensitive period for vocal production learning6, song culture appears as a multi-generational phenotype, partially encoded in the genes of an isolated founding population. In this species, juvenile birds, that imitate isolated tutors, changed particular characteristics of the songs. These alterations can be accumulated over learning generations until a new natural song emerges7.Vocal signals often play a critical role in animal communication8, and individuals of other species can learn the context in which to produce a particular call or how to modify their response to others’ vocalizations9. Communication using songs is widespread in different groups of birds and marine mammals, but is rare in primates10. A key question is to what extent primate vocalizations can be shaped by vocal production learning processes  and social factors, and whether they may possess information useful for kin recognition. The current evidence is contradictory, with data suggesting both vocal learning and genetic relatedness as forces in shaping primate vocal signals. For instance, Marshall and colleagues11 suggested that genetic relatedness had a limited effect on the acoustic similarity in chimpanzee’s vocalizations (Pan troglodytes), since unrelated males showed a similar acoustic structure in their pant hoots. Further studies on chimpanzees consolidated the idea that vocal learning and convergence may play a role in the acoustic structure of food grunts shared within two groups12. The influence of social factors in shaping vocal signals has also been suggested for monkeys. Lemasson and colleagues found that social bonding better explained the acoustic similarity in the vocalizations of Campbell’s monkeys (Cercopithecus campbelli) when compared to genetic relatedness13. Although evidence seems to suggest that primate calls are not completely genetically determined, the question whether information about genetic relatedness, crucial for kin recognition, is retained in vocalization is still open. A study of mandrill’s vocalizations (Mandrillus sphinx)14 showed that the acoustic structure of contact calls was more similar between relatives than among unrelated individuals, suggesting that mandrill acoustic signals contain kin-specific information.Although birds are the only animals in which vocal production learning has been rigorously associated with the modification of the cerebral connections, previous research showed that learning in vocal communication is not unique to them. Some terrestrial and marine mammals may possess the ability to learn the production of particular emissions15) is of great interest. Unfortunately, limited knowledge about the ontogenesis of primate singing behavior prevents a proper comparison with studies on birdsongs. However, previous research on gibbons reported that juveniles and young females produce immature vocalizations (Hylobates lar and H. agilis16) and that the structure of the songs may reach a mature form at about six years old (Nomascus gabriellae17). Moreover, the co-singing of mothers and daughters in Hylobates agilis has been interpreted as a possible form of tutoring to switch from an immature to a mature female great call18. On the other hand, concordance between song and genetic diversity across the crested gibbons19 suggests that genes may play a major role in shaping song structure. Additionally, both hybrid males and females showed intermediate song structure compared to the songs of the parental species . Interestingly, female songs tended to diverge more from their parents’ songs, while males’ appeared to resemble those of their father.Because vocal learning has been typically associated with singing, studying the effects of genetics and social factors on the vocal output of primates that communicate using songs  and distantly related indris in the population of Maromizaha.Indri indri22) is the only lemur that communicates through songs. The indris’ songs are long sequences of vocal units that are organized in phrases24. They have the form of a chorus in which all the adults and the subadults of a group utter their contribution in a precise and coordinated manner25. Songs have various functions depending on the context in which are emitted and they are used for both inter and intra-group communication27. Furthermore, songs are likely to provide information about the group composition and mediate the formation of new groups29. Because this species lives in familiar groups  and the song has a rich repertoire of units31, the indris can be an excellent model to investigate the relationship between genetic relatedness and song similarity. Recent studies by Gamba and colleagues25 showed that the acoustic structure of phrases did not significantly change between age classes, suggesting that a limited variation may occur during ontogeny.The indri  finding that their songs differed markedly from the song characteristics of the parent species. However, studies on ground squirrels (Spermophilus suslicus) found a weak correlation between acoustic similarity and kinship, showing that other factors, such as the need for an individually distinctive acoustic structure, may play a critical role in vocal communication34.The inheritance of song characteristics has been inferred from the studies of hybrid gibbons. Geissmann37. In this second scenario, measures of genetic relatedness are not associated with song traits and we predicted that genetic distance and song similarity should not covary, but individuality and group membership would instead explain most of the acoustic variation.In this study, we hypothesize that, if genetics strongly determines song characteristics, vocal learning may not play an important role in shaping the indris’ songs. We predicted that if song traits are mainly inherited, a high genetic distance will correspond to a reduced song similarity and that this reduction would be consistent within and between sexes. But it is also possible that emitters possess the potential for modifying their utterances and use songs to advertise their individuality and their belonging to a groupFour principal components accounted for 83.2% of the total variance of the temporal variables of the descending phrases of two units  Table . DP2s anIn contrast, indris produced phrases that did not signal group membership accurately. In fact, pDFAs using the temporal and frequency parameters of DP2 and DP3 showed statistically significant p-values neither during the training, nor during the testing (Table Mandrillus sphinx14). It is interesting to notice that the encoding of this information is strong in the temporal characteristics of the descending phrases when analyzed using genetic similarity indices, but significantly stronger in both temporal and frequency parameters of DP2 and DP3 when compared between related and unrelated males. The correlation between temporal patterns and genetic relatedness is especially interesting in the light of those studies that investigated how hybrids differed from their parental species in the acoustic characteristics of their utterances39. In gibbons and lemurs, pulse structure and rhythmic characteristics have a particular relevance in the discrimination between hybrids and parental species38. Our results are in agreement with analyses of intra-population variation on ground squirrels (Urocitellus beldingi) showing that individuals produce calls more similar to their relatives than to unrelated individuals40. We extended these findings showing that, in indri, relatedness is also encoded by frequency parameters of both DP2 and DP3 in males, and DP2 in females.The results presented here come from the first intra-population analysis of indris comparing the acoustic characteristics of song phrases and genetic relatedness. Using this approach, we demonstrated that the structure of males’ phrases transmits information about relatedness more consistently than females’ ones, and that song phrases possess the potential to provide conspecifics with a cue to individual identity of the emitter in both sexes. Male song-phrases DP2 transmit information about relatedness in the form of time parameters, but this information is not encoded in female calls. We found a tendency for encoding of relatedness information in the frequency structure of male song-phrases DP3. We also found that similarity of both temporal and frequency parameters in male phrases DP2 and DP3 correlate significantly correlate with genetic distance in the ‘father-son’ category. A result that for female phrases is limited only to the frequency parameters of DP2. We did not find significant correlations across sexes. Overall, we can confirm our prediction that the indris’ song phrases contain information about genetic relatedness as it has been found in other primate species  possess patrilineal signatures that mediate paternal kin recognition. Male vocal signatures have been indicated as an important mechanism for inbreeding avoidance43. This mechanism may have sense in the light of the long-term pair bonding of indris44, but may also play a role in a scenario in which extra-pair copulation can potentially contribute to increasing levels of genetic diversity within a population45. Moreover, even though physical fights between individuals of neighboring groups are rare in indris46, they involve primarily males and always include choral vocal displays47. Thus, song similarity between related males may mediate kin recognition and de-escalate aggressions. From a different perspective, the descending phrases are paradigmatic examples of vocal emissions with remarkable frequency modulation23. It is therefore possible that those phrases are acoustically more flexible and less genetically-determined. This interpretation can explain only part of our results, but it is interesting to notice that in the study by Lemasson and colleagues48 the genetic similarity between Campbell’s monkey females (Cercopithecus campbelli campbelli) did not explain the acoustic similarities of their contact calls. A higher degree of acoustic plasticity within females is supported by previous research on baboons , Campbell’s monkeys (Cercopithecus campbelli campbelli50), and Japanese macaques (Macaca fuscata51). Whether social factors may play a role in the acoustic plasticity of female indris need further investigation, but there is evidence that the contribution of the temporal structure to the song is less genetically determined in females than in males. Previous studies have found that females change the duration of their song to partially overlap with males’ singing29. Females may also adjust duration according to the number of males in their social group, while males tend to avoid overlapping each other26.While the vast amount of data about primate kin recognition is devoted to the highly complex social groups of African monkeys52 that data from the field do not support for the indris. Data collected over 14 years and in different forests suggest that both male and female indris disperse , although dispersal frequency and distance are currently not available.The lack of knowledge about dispersal patterns in the indris prevents further speculation regarding the relatively higher genetic signature in male calls. In socially monogamous species there is a tendency towards female-biased dispersal53. Previous research has demonstrated that sex differences may override individual differences25, but the results of the present study complement those findings showing that strong individuality is nevertheless encoded in the indris’ phrases. The presence of an individual signature is confirmed by both the training and testing phase of the permuted Discriminant analysis and it is valid for both temporal and frequency parameters. Our findings are in agreement with previous studies that have reported a strong individual signature in the acoustic signals of social mammals . The individuality encoding was also found in the Cao Vit gibbon male phrases55 and in the Bornean gibbon female great calls56, two species that emit songs like the indris. Our analyses suggest that individuality is encoded in both males and females, tracing an interesting path for future research in other singing primates. While most of the previous research on the indris’ song suggests that the temporal parameters play a major role in the sex-specific encoding of the vocal emissions29, we found that also frequency parameters have potential for individual recognition. This evidence expands the recent findings of Gamba and colleagues25 about a sex-specific difference in pitch patterns during the song. In general, both time and frequency variables appeared to play a role in encoding individuality as they probably do for sex-specificity.Individual variation in the vocal signals is a precondition for individual recognition, which can result in both affiliative and aggressive situations46. This idea is in agreement with previous studies on other primates, where long distance vocalizations were found to be useful for identifying individuals55 and estimating male fighting ability57. Although we do not have data in support of the hypothesis that song may be useful to estimate individuals’ fighting ability, our behavioral observations suggest that they indris can vocally discriminate individuals. Two lines of evidence support this idea. Torti and colleagues26 showed that songs elicited regrouping of particular individuals within a group. Bonadonna and colleagues45 observed that a female that has just been involved in extra-pair copulation did not join the song of her group mates, which were singing at a distance. We found support for the hypothesis that the use of song phrases to broadcast individuality may be essential during pair formation at distance26 and for the regulation of territorial spacing, where other communicative signals may be ineffective58.Behavioral observations support our results that singing in indris may facilitate the exchange of identity information in the context of distant communicationSaccopteryx bilineata59) and Vester and colleagues on pilot whales , where differences of vocalizations within social groups were significantly lower than intergroup differences. The work on the greater sac-winged bats is particularly interesting because the authors found that pups modified their emissions during ontogeny and learned their songs through vocal imitation of their harem males, independently of their genetic relatedness59. Studies on apes and monkeys suggested a consistent degree of acoustic plasticity in nonhuman primate calls, which was observed in particular after social changes62 or during vocal interactions63.When we analyzed the dissimilarity of phrases emitted by members of a social group, we found that pDFA could assign neither DP2 nor DP3 to the group with a classification rate higher that those predicted by chance. This result is in contrast to the findings of Knörnschild and colleagues on greater sac-winged bats . Future playbacks of the indris’ songs may improve our knowledge about the amount of information encoded by the songs.A previous investigation on the rhythmic structure of the indris’ song showed that the structure of the descending phrases did not change significantly during ontogenyOverall, our results confirm that vocal signals can be shaped by both genetic factors and social experience in the indris. Even in primates that emit songs with complex temporal and frequency patterns, phrases contain information about genetic relatedness and subtle variation in the acoustic structure may play a role in providing conspecifics with cues for kin identification and individual discrimination.65, we were able to attribute each vocalization to a signaler. From the individual song contributions, we extracted 1066 descending phrases consisting of two units , and 1259 descending phrases consisting of three units , seven siring females, 9 offspring . We collected data in the field from 2011 to 2016, for a total of 24 months. We observed a social group per day, approximately from 6 AM to 1 PM. We identified the indris individually thanks to natural marks. Group composition ranged from 2 to 4 indris  with the following changes from the manufacturer’s protocol (QIAamp DNA Stoll Handbook 04/2010). We used 300 mg stool; we added 35 μl of proteinase K and incubated at 70° Celsius for 30 minutes during the purification phase. We applied 75 μl Buffer AE on the QIAamp membrane for the first DNA elution and incubated the spin column with Buffer AE at room temperature for 15 minutes.For the samples collected in 2014, we used the automated robotic workstation QIAcube HT supported by the software QIAxtractor 4.17.1 (Qiagen®) to conduct DNA purification. We set the protocol for QXT Liquid DNA V1. First, we bathed the 2.0 mL tubes containing 300 mg of smashed feces and 1.6 mL of Buffer ASL at 70 °C for at least 5 minutes. After that, tubes were centrifuged at 13000 RPM for 10 minutes. We transferred 200 μl of supernatant to separate wells of the QIAextractor lysis plate and we started the run. At the end of the process, we obtained 70 µl of DNA elution for each sample. We stored the extracted DNA at 4 °C for immediate use.67 . We mixed 1 µL of PCR product with 6.85 µL HiDi formamide (Applied Biosystems) and 0.15 µL Genescan 500-ROX size standard (Applied Biosystems). We conducted automated allele calling using the software GENEMAPPER 3.7 (Applied Biosystems). We then confirmed by eye all the allele sizes and checked for consistency across replicate PCRs of the same sample or from the same individual for a certain locus (minimum three replicates for heterozygotes and five replicates for homozygotes).related68. First, we compared seven different relatedness estimators commonly used in the literature, five moment estimators73 and two likelihood-based estimators, the dyadic likelihood estimator – dyadml74 and the triadic likelihood estimator – trioml75. Using the allele frequencies observed in our dataset, we simulated datasets of 100 pairs for four known relatedness categories . We chose the trioml75 estimator to calculate relatedness for all possible dyadic combinations because it showed the highest consistency and obtained a matrix in which the more positive the index, the more two individuals are genetically related. Since indri lives in family group47, the historical record of group composition since 2009 allowed us to infer parental relationships among individuals based on behavioral observations, especially between mother and offspring. We were able to assign a social father to each of the offspring included in the study. To define parental information for the comparison of acoustic distances, we run paternity analyses including as potential fathers all the adult males sampled  and could assign paternity for nine offspring (out of 10).We estimated relatedness among individuals using the R package 76. We then added 0.5 s of silence at the beginning and the end of each phrase. Because each unit within a phrase went through the same set of measurements, we collected a minimum of 10 measurements in the temporal domain and a minimum of 20 measurements of pitch variability for each DP. The complete list of variables we measured is in Supplementary Table 25.Because the singers’ phrases could overlap each in the temporal and frequency domain, we first extracted the fundamental frequency using a manual procedure and then obtained the pitch contour using a semi-automatic process in Praatdist in R 3.2.3) and then calculated the average individual means. We then run the Mantel tests (9999 randomizations78) on the average individual means against the matrix of genetic indices (package vegan in R79). All matrix indices were normalized to have a value between 0 and 1 before entering the analyses.We used principal components analysis  to reduce the data to uncorrelated principal components (PCs) using separately temporal and frequency measurements of DP2s and DP3s. We obtained four PCs exceeding eigenvalue 1 for the temporal measurements and five for frequency variables of DP2s. We obtained six PCs exceeding eigenvalue 1 for each of the two sets of variables of DP3s. To understand whether genetic relatedness could explain acoustic similarities, we transformed the PCs obtained for each of these sets in a Euclidean distance matrix . We assessed the correlation between the acoustic similarity matrix and a binary matrix indicating the category . When testing for individual differences, we used the individual as test factor and the song from which the DPs were extracted as a control factor. We also ran the analyses split by sex. When testing for group membership, we used the group as test factor and the individual identity as control factor. We split all the analyses into two phases, a training phase and a testing phase  for which we collected the correct classification rate and the p-value.To understand whether we could identify a potential for individual recognition or group membership we submitted the component scores to permutated linear discriminant function analysisData and programs used for the analyses presented in the paper are available to the Editorial board members and the referees upon request or already included in the Supporting Information.Supplementary Information


STAT3  is a transcription factor in the JAK/STAT signaling pathway in response to extracellular cytokines and growth factors . STAT3 i50 of 3.2-5.4 μM in multiple cancer cell lines by inhibiting STAT3-dependent gene expression and inducing apoptosis [DBDs of transcription factors and DNA damage repair proteins are generally considered “undruggable” with flat and similar surface areas , 7, whic50 of 1.8-5.3 μM against multiple cancer cell lines. These active analogues were not only selective to STAT3 over STAT1 as demonstrated using electrophoretic mobility shift assay, they had no effect on the survival of STAT3-null hematopoietic progenitor cells, suggesting that they are likely specific to STAT3. One of the effective analogues, inS3-54A18, was selected as a lead compound because it was soluble in a proprietary oral formulation suitable for in-vivo study and demonstrated to not only effectively inhibit cancer cell survival, but also inhibited migration and invasion of cancer cells, the in-situ DNA-binding activity of STAT3, and the growth and metastasis of xenograft tumors in vivo with repeated oral dosing.To improve the pharmacokinetic properties of inS3-54, Huang et al. [Huang et al. also conducted structure-activity relationship analysis of all analogues , which rAlthough many inhibitors targeting the SH2 domain of STAT3 have previously been reported, most of these studies provided no direct evidence that these inhibitors indeed bind to the intended targeting site. In contrast, direct and specific binding to the DBD of STAT3 by the DBD-targeting inhibitors was validated by Huang et al.  using imThese findings on inhibitors targeting the DBD of STAT3 by Huang et al. , 5 not o


Background: The gold standard for diagnosing excessive tracheal collapse is still evaluation during bronchoscopy. Today, multidetector computed tomography (MDCT) is used to confirm a suspicion of abnormal tracheal collapse. There is no gold standard for computed tomography (CT) image analysis of tracheal collapse.Purpose: To evaluate four different methods for the diagnosis of tracheal collapse using the images obtained through MDCT to help clinicians evaluate the images in daily practice.Objectives: 374 consecutive high-resolution CT scans with full inspiratory and end-expiratory CT scans were retrospectively analyzed.Methods: The images were analyzed in four different ways. The degree of collapse was based on cross-sectional areas of individual locations or volumes of entire regions: (1) 1 cm above the carina, (2) the level of maximal collapse of the trachea, (3) the entire region from the carina to the thoracic inlet, and (4) the trachea and bronchial region as defined by the software.Results: We compared three existing and one new method for image analysis of tracheal collapse by MDCT. The prevalence of tracheal collapse varied from 10.7% to 19.5% in this cohort of patients suffering from mixed lung diseases when using an expiratory collapse of ≥50% as a threshold. The four methods were comparable with highly significant Pearsons correlation coefficients (0.764–0.856). However, the four methods identified different patients with collapse of ≥50%. There was no correlation between symptoms and the degree of collapse.Conclusion: The different methods identify tracheal collapse in different patients. Hence, the diagnosis of excessive tracheal collapse can not rely solely on MDCT images. Generally, there is a poor correlation between symptoms and the degree of collapse in the different methods. However, when using the maximal collapse, there is some correlation with symptoms. When in doubt regarding the diagnosis, further investigations, such as bronchoscopy, should be carried out. Excessive tracheal collapse is characterized by flaccidity of the tracheal wall resulting in expiratory collapse of ≥50% of the central airways. The most frequent symptoms of tracheal collapse are cough, dyspnea, wheezing, and recurrent infections. This complicates diagnosis, as it mimics other and more common lung diseases .10.1080/The reported prevalence of tracheal collapse varies in different studies and depends both on the method used for diagnosing tracheomalacia and on the comorbidities of the patients –5. The hThe gold standard for diagnosing excessive tracheal collapse is still evaluation of the cross-sectional area of the trachea before and at forced expiration or cough during bronchoscopy. Until recently, this was the only available diagnostic option. With the introduction of multidetector computed tomography (MDCT), a non-invasive diagnostic tool is now available. This new tool poses new challenges such as standardization of a scanning protocol, standardization of image analysis, definition of the degree of airways collapse, and determination of the threshold for normal/abnormal airway collapse. Several methods for tracheal collapse evaluation of MDCT images have previously been used –8. The mThere is no gold standard for computed tomography (CT) images analysis of tracheal collapse. To our knowledge, no studies have previously compared different image analysis methods with respect to identification of tracheal collapse. The aim of the present study was therefore to compare four different methods of high-resolution CT image analysis for tracheal collapse to help the clinician to appraise the CT images in the daily practice.This study was approved by the Danish Data Protection Agency. During a 17-month period, 374 patients were referred to a high-resolution computed tomography (HRCT) scan performed in full inspiration and in end expiration. No participants were recruited exclusively for this study. The volume of tracheal collapse was measured retrospectively. The indication for HRCT is shown in Patient files were scrutinized for data on age, respiratory symptoms , smoking history, body mass index and pulmonary function data  at 3 months before and 3 months after the HRCT. Pulmonary function tests were analyzed in accordance with American Thoracic Society and European Respiratory Society guidelines  Table 2Table 2.1HRCT was performed on a multirow detector scanner  and included a scan range of the whole chest in full inspiration and at end expiration. The CT acquisition parameters were 64 × 0.625 mm or 126 × 0.625 mm collimation, kV 120, mAs/slice 150–200, rotation time 0.5 s, pitch 0.59, reconstruction thickness 0.9 mm, and increment 0.45 mm. A high-resolution kernel was used. Images were transferred to a picture-archiving communication system.During the scanning acquisition, an automatic voice recording instructed the patients to take a deep breath and hold it for end-inspiratory scanning. For end-expiratory scanning, the patients were instructed to take a deep breath, exhale, and hold it.Image assessment was performed on a dedicated CT workstation  using standard lung window display settings (level: –500  hounsfield units (HU); width: 1500 HU). The images were retrospectively analyzed by a registrar in pulmonary medicine . Four different methods for calculation of tracheal collapse were performed:The volume of a 10 mm CT slice located 1 cm above the carina as shown in The volume of 10 mm CT slices from the level of the carina and every 1 cm until the thoracic inlet was examined. The location with maximal collapse was chosen as depicted in Each 10 mm slice from the carina to the thoracic outlet was manually defined on both inspiratory and expiratory scans. The sum of these volumes was multiplied .An automatic software segmentation technique of the lungs and the large airways was used to estimate the volume of the trachea  in the inspiratory and expiratory scan . The upp[/luminal area or volume at inspiration] × 100%The relative collapse in expiration was calculated as:Normal distribution of all variables was confirmed by Q–Q plots. The correlation between the different methods was primarily evaluated using Bland–Altman plots. Afterwards, the Pearson correlation coefficient was used to evaluate the correlation between the different strategies for analyzing the images.t-test. The tests are considered one-sided, as an excessive tracheal collapse never would lead to an improvement in the pulmonary function tests. The categorical variables were analyzed using the chi-square analysis.Sample characteristics were examined, and continuous variables were compared by the unpaired p < 0.05 for all statistical analyses. All analyses were performed using statistical software .The level of significance was set at A total of 353 HRCT scans met the inclusion criteria. The cohort consisted of 191 females  and 150 males . Patient demographics are listed in p < 0.001). Using an expiratory collapse of 80% as threshold, only 1–3 patients were identified, and the prevalence decreased to <1% for all four methods.The prevalence of tracheal collapse varied from 10.7% to 19.5% when using an expiratory collapse of 50% as a threshold . The prep = 0.289–0.817, chi-square analysis) using three out of four methods.There was no significant difference between the prevalence of abnormal collapse in the three major lung disease groups: asthma (4.55–19.57), chronic obstructive pulmonary disease (COPD) (10.42–28.30), and interstitial lung diseases (13.33–19.75)  to determine the localization of maximal expiratory collapse (Method 2). The maximal collapse was located at the carina in 27% of patients . When evr = 0.764 and r = 0.856 (p < 0.001).Correlations between the four different methods for measuring tracheal collapse were analyzed using Bland–Altman plots. The plots were acceptable with a systematic difference between the methods (mean difference between 0.3 and 11 depending on compared methods). These results allowed us to use the pairwise linear regression analysis. The Pearson correlations were between p = 0.014 and p = 0.028). In method 2 and method 4, the difference was just insignificant (p = 0.056).Patients with expiratory tracheal collapse of ≥50% were significantly older than patients without collapse (63 years contra 56 years), and apparent for all four measuring methods . For botp < 0.05). They also showed a trend toward recurrent infections, albeit not insignificant (p = 0.07). The other methods revealed no significant relation between a tracheal collapse of 50% and dyspnea, recurrent infections, or cough . When using method 1 (1 cm above the carina) and method 4 (volume given by the software), there was no difference.The relationship between three common respiratory symptoms, cough, dyspnea, and recurrent respiratory infections, and tracheal collapse, was evaluated. Significantly more patients in the group with collapse of ≥50% had dyspnea using method 2 (or cough . The BMIp = 0.06 and p = 0.09) lower in the group with tracheal collapse compared with the patients with normal tracheal function. The patients with tracheal collapse of ≥50% had a tendency toward oscillations on the flow-volume loops. In methods 1 and 4, the number of flow-volume loops with oscillations was significantly higher in the group with abnormal collapse (≥ 50%) than in the group with less collapsibility (p = 0.01 and p = 0.005). In method 2, there was a trend (p = 0.06).There was no correlation between expiratory tracheal collapse and lung function tests using any of the four image-analysis methods (Table 3). However, we noticed a trend toward a correlation between the tracheal collapse and the FEV1 and FVC when using method 2. The FEV1 and FVC were insignificantly , but did not identify the same patients. Different groups of patients with airway collapse of ≥50% were identified depending on the method used for image analysis. Hence, in the clinical practice, it is important not to rely solely on the results of the MDCT but to investigate further, if there is a clinical suspicion of excessive tracheal collapse. There is no significant correlation between the degree of collapse seen on MDCT and clinical symptoms, making the diagnosis even harder. However, the correlation between the degree of collapse and symptoms has never been established in bronchoscopy either. In The prevalence of tracheal collapse in our cohort of patients with different lung diseases ranged from 10.7% to 19.5% depending on the method used for image analysis. Previously, other characteristics have been included in the diagnosis such as in the multidimensional classification system Functional status, Extent, Morfology, Origin and Severity of the abnormalities (FEMOS) that includes symptoms, etiology, morphology, extent, and severity of the collapse .The method resulting in the highest prevalence of abnormal collapse is naturally the one using the maximal collapse at a certain level. In our study, the area with maximal collapse is based on measurements of the cross-sectional areas from the carina to the thoracic inlet. In a study by Lee et al., a radiologist determined the maximal collapse visually, while Ochs et al. used a technique similar to ours that minimizes the interobserver variation ,14. An ip = 0.07), low FEV1 (p = 0.06), and FVC (p = 0.09) in the group with significant tracheal collapse. Methods 1 and 2 using only one location for evaluation of the collapsibility are rapid and easily performed. Previous studies have most often used the location 1 cm above the aortic arch for evaluation [The method using the maximal collapse (Method 2) was the only method that revealed a significant correlation between symptoms and tracheal collapse. There was a higher percentage of patients suffering from dyspnea in the group of patients with tracheal collapse of ≥50% by the use of this method. Furthermore, there was a trend toward a higher risk of recurrent infections p = 0.0, low FEVC p = 0.0 in the galuation . HoweverThe method using the cross-sectional areas from the carina to the thoracic inlet is more time-consuming with more interobserver variation, but the advantage is that the whole trachea is evaluated, thus providing information about both the severity and the disease extent.No readers of CT scans can rely only on software results. Some patients have extensive collapse making segmentation by the software impossible, and thus the radiologist has to evaluate pronounced collapse or consider other reasons for the inability for an automatic segmentation. However, when feasible, the fully automatic method is rapid without interobserver variation. Inherently, the inability of the software to generate the volume of the trachea in case of severe collapse poses major problems, as the most severely affected patients are not identified. Consequently, the correlation with symptoms and pulmonary function tests is low when using this method.All analysis methods found a significantly higher mean age in the group with tracheal collapse above 50% compared with the group with less collapse. It is tempting to impute the weakness of the tracheal wall to the general degenerative process of aging, but this needs to be proven. The patients with tracheal collapse had a higher mean BMI. It is questionable whether a difference in mean BMI of 1.5 is of clinical importance. However, this is in accordance with a recent study reporting a significantly higher degree of collapse in patients with COPD and a BMI ≥ 35 . A highePrevious studies have suggested 80% as the threshold for excessive tracheal collapse . In our We acknowledge that there are several limitations in our study. The study is retrospective and observational in design. The indication for the MDCT scans was not to evaluate the collapsibility of the trachea. Our study is based on MDCT scans performed to diagnose a broad variety of lung diseases. The frequency of tracheal collapse was the same in obstructive airway diseases (asthma and COPD) and interstitial lung disease. The expiratory images were obtained at end expiration instead of during forced expiration, which was previously shown to lower the prevalence . We beliIn conclusion, we have evaluated four different methods for the diagnosis of tracheal collapse using MDCT scanning. The different methods identify tracheal collapse in different patients depending on the method used. It is important to emphasize that there is a poor agreement between the four methods used for image analysis and a weak correlation between symptoms and degree of collapse. The software-generated results are easy and without interobserver variability, but do not identify severe collapse, thus making its use limited. The method using maximal collapse to identify patients reveals some correlations with both symptoms and pulmonary function tests, thus making this the method of choice for evaluating tracheal collapse on MDCT images. Research is warranted to determine which method correlates better with bronchoscopy, PFTs, or symptoms of tracheal collapse. A future study is planned to evaluate the tracheal collapse in expiration using both bronchoscopy and MDCT in different groups of patients suffering from known lung diseases. The correlation between the bronchoscopic results and the different image analysis will be examined and related to symptoms and pulmonary function tests.It is still uncertain if tracheal collapse is an independent concurrent disease, a comorbidity, or a consequence of an underlying lung disease, and prospective studies are warranted.


Mytilus spp., are ecosystem engineers in the coastal zone globally. To improve knowledge of distribution and genetic structure of the Mytilus edulis complex in the Arctic, we analyzed 81 SNPs in 534 Mytilus spp. individuals sampled at 13 sites to provide baseline data for distribution and genetic variation of Mytilus mussels in the European Arctic. Mytilus edulis was the most abundant species found with a clear genetic split between populations in Greenland and the Eastern Atlantic. Surprisingly, analyses revealed the presence of Mytilus trossulus in high Arctic NW Greenland (77°N) and Mytilus galloprovincialis or their hybrids in SW Greenland, Svalbard, and the Pechora Sea. Furthermore, a high degree of hybridization and introgression between species was observed. Our study highlights the importance of distinguishing between congener species, which can display local adaptation and suggests that information on dispersal routes and barriers is essential for accurate predictions of regional susceptibility to range expansions or invasions of boreal species in the Arctic.Climate changes in the Arctic are predicted to alter distributions of marine species. However, such changes are difficult to quantify because information on present species distribution and the genetic variation within species is lacking or poorly examined. Blue mussels,  Temperatures in the Arctic are estimated to increase by 4–7°C over the next century, with wide‐ranging effects on Arctic species ACIA . This haMytilus are frequently used as environmental indicators, as they are semi‐sessile, have a relatively long life span, and are widely distributed in coastal regions in both Northern Hemisphere and Southern Hemisphere  have been performed  through the Bering Strait ; M. edulis populations on each side of the Atlantic are genetically distinct  or in 96% ethanol at 4°C . Measurements of shell length, width, and height of frozen mussels were conducted at the laboratory facilities at DTU Aqua in Silkeborg, Denmark, whereas the measurements of ethanol preserved specimens were taken at the sampling locations.M. trossulus and M. galloprovincialis were provided from the Sea of Okhotsk, Russia, and from around Galician Rías in NW Spain, respectively, to evaluate the species status of the sampled mussels and to identify potential hybrids.Reference samples of 2.2A minimum of 30 mg (wet weight) of mantle tissue was dissected from each mussel, and DNA was extracted using the Omega EZNA Tissue DNA kit  according to the manufacturer's instructions for tissue. DNA content in the extracts was verified on a NanoDrop spectrophotometer .2.3Mytilus spp. genetic structure  study ERP006912) at the University of Stirling (Table S1).SNP genotyping was conducted using the Fluidigm Biomark™ HD System. 96.96 Dynamic Array IFCs were read on a real‐time PCR system after amplification and scored using Fluidigm SNP Genotyping Analysis software. The samples were genotyped for a panel of 96 SNPs: 19 from previous publications on 2.4He) and observed (Ho) heterozygosities. This was done for both the full data set and for a reduced data set consisting exclusively of inferred M. edulis individuals (see explanation in section on M. edulis population structure below). Overall and pairwise FST values for all samples were estimated in Genepop 4.2. This initial sorting and discarding of SNP loci resulted in 81 loci being retained for further analyses. As most SNP loci were developed from M. edulis, reliable scoring of M. trossulus individuals was not possible for three loci , and analyses concerning hybrid identification were performed for 78 SNP loci only.Loci with more than 25% missing data across all samples were discarded. Genepop 4.2  for grouping individuals. This was also done to positively identify M. edulis individuals and subsequently create a reduced data set exclusively aimed at investigating population structure within this species. Considering the close genetic resemblance of Mytilus spp. and the assumed low gene flow between geographically distant samples . Separate simulations were conducted for M. edulis samples from Greenland  and the Eastern Atlantic (WS2). The simulated and real individuals were included in a common Structure run (K = 4) and 95% confidence intervals for the inferred ancestry of the simulated individuals were recorded and compared to the real individuals.Based on the generated pairwise Grønkjær  using thGrønkjær . Briefly2.6M. edulis. Based on the results from the analysis of simulated parentals and hybrids (see results section), we chose to only include individuals with admixture proportions below 0.2, as estimated by Structure. This was done to avoid extensive influence of hybridization on estimates of population divergence, but at the same time allowing for statistical uncertainty regarding whether individuals were pure M. edulis individuals or not. No significant differentiation was found between sampled mussels of different size classes from the same location . Consequently, they were pooled prior to downstream analyses of population structure. Pairwise FST estimates were generated with Genepop 4.2, while Structure v2.3.4 was used to estimate the most likely number of genetic clusters. A burn‐in period of 50,000 iterations was chosen followed by 100,000 MCMC repetitions for K values 2–4. A hierarchical AMOVA was conducted in Arlequin v.3.5.2.2 . To visualize the genetically based grouping of M. edulis population samples, a multidimensional scaling plot was generated, while a principal component analysis, PCA, was used to illustrate the relationships among M. edulis individuals in general and specifically for the Norwegian, Svalbard, and Russian samples to infer the likely origin of Svalbard mussels. The PCA scatter plots were generated in R, using the cmdscale function and the package Adegenet.A reduced data set was used to assess the population structure in 2.7Mytilus edulis” data set, the joint distribution of FST and heterozygosity under a hierarchical island model of population structure was examined using Arlequin v.3.5.2.2 . The analytical settings for generating 95% and 99% confidence intervals were 20,000 simulations, 100 demes per group, and 10 groups. Loci outside the 95% quantile were considered possible subjects to selection, as these loci deviate more than could be expected under a model of neutral population structure. From this analysis, an exclusive “outlier” data set and a “neutral” data set were created to test the importance of outlier loci for defining the inferred population structure of M. edulis; that is, the true connectivity among populations based on neutral processes (drift and migration) could be obscured by loci under divergent selection. For both data sets, overall and pairwise FST estimates were generated in Genepop 4.2, while Structure v2.3.4 with K = 2 (using settings as above) was used to investigate whether the population structure found in M. edulis based on all loci could be identified from both the “outlier” and “neutral” data sets, or whether they displayed contrasting patterns.To identify loci potentially under selection in the “33.1Three loci  deviated significantly from HWE in ten samples or more, and they were discarded from further analyses.In total, 73,206 pairwise tests for LD between loci within samples were performed of which 3,194 tests were significant (4.36%). On average, 154 of 3,485 tests were significant within samples (range 0–986 significant tests). Only three SNP pairs displayed significant LD in more than five samples: 137120_A x BM8E (significant in six samples), 100078_A x 40154_A (significant in eight samples), and 175018_A x 241544_A (significant in 12 samples). Subsequently, one locus from each of the coupled SNP pairs was discarded  to eliminate effects of linkage on downstream analyses.He and Ho (Table Ho was close to He except for the Upernavik sample (UPE), where He and Ho was 0.25 and 0.14, respectively, and one of the White Sea samples (WS1) with He and Ho of 0.32 and 0.24. In the reduced data set, with samples consisting only of inferred M. edulis, individuals provided estimates of allelic richness between 1.57 and 1.67  with the highest pairwise FST value between the M. trossulus and M. galloprovincialis reference samples. Further, high values were found between M. galloprovincialis and the N Greenland samples from Qaanaaq; QAS and QAL (0.738 and 0.774) and between M. trossulus and all other samples except the three N Greenland samples .The overall 3.2M. trossulus (MTR) and M. galloprovincialis (MGA). The majority of samples clustered together in a “M. edulis” cluster. However, the QAS and QAL samples clustered with the M. trossulus reference sample, while samples UPE, WS1, and Lofoten (LOF) were located between the three main “species” clusters. UPE and WS1 appeared to be distributed between the M. trossulus and M. edulis clusters, while LOF was situated between the “M. edulis” and “M. galloprovincialis” clusters. The clustering of QAS and QAL with MTR, and the inferred separation of UPE, WS1, and LOF from the “M. edulis” cluster were further supported by the principal component analysis scatter plot of individual genotypes , with few individuals (3–4) showing evidence of M. edulis hybridization. Only two samples, UPE and WS1, contained both pure M. edulis and M. trossulus individuals. The UPE sample contained approximately 51% M. trossulus and 33% M. edulis and 14% M. edulis/M. trossulus hybrids, while the WS1 sample was comprised of 9% M. trossulus, 80% M. edulis, 9% M. edulis/M. trossulus hybrids, and 2% M. edulis/M. galloprovincialis hybrids. The distribution of M. galloprovincialis individuals is mainly restricted to samples from the Norwegian coast and the Svalbard archipelago . A single apparent M. galloprovincialis individual was found in the sample of large mussels from Nuuk (NUL). The LOF sample contained the highest number of M. galloprovincialis observed—64% and further 11% M. edulis and 22% M. edulis/M. galloprovincialis hybrids. In cases where more than a few hybrids were found, the distribution of admixture estimates of real individuals was compared to the simulated hybrids. In all cases, different classes of hybrids  were suggested. However, as explained above the comparison of real and simulated individuals should be interpreted with caution.The inferred proportion (using the 20% criterion) of the different les Fig.  show tha3.3FST for all samples identified as M. edulis was 0.048. Pairwise FST values ranged from 0 to 0.113 with the highest values between the Greenlandic samples and the Norwegian, Svalbard, and Russian samples (Table S3). The lowest FST values were found between geographically proximate samples such as the two White Sea samples (WS1 and WS2) and the two sampling sites in Svalbard (SVA and SV4). For sites with samples of different size classes, FST estimates ranged between 0.001 for the Nuuk samples (NUS and NUL) and 0.018 for the Tromsø samples (TRS and TRL) (Supplementary Table S3). The low FST for Nuuk samples indicates short‐term temporal stability of genetic population structure. The higher FST estimate for Tromsø mussels was not significant, thus allowing the pooling of size classes for the downstream analyses.The overall Mytilus edulis” data set (K = 2–4) showed a clear clustering of samples, essentially separating the Greenlandic samples from the other samples  Greenlandic samples, (ii) Norwegian, Svalbard, and Russian samples, and (iii) the Icelandic sample found between the two main clusters inferred by axis 1.The hierarchical AMOVA for the three groups  provided an estimated variance of 5.78% among groups and 0.43% among samples within groups. The multidimensional scaling plot of population samples Fig. B and theThe principal component analysis scatter plot including only Norwegian, Svalbard, and Russian samples Fig. C did not3.4FST outliers, with six loci significant at the 5% level and three at the 1% level. All of these outliers are high FST outliers . The Structure analyses for both the “neutral” and “outlier” data set also supported the initial population structure separating Greenlandic samples from the Norwegian, Svalbard, and Russian samples and with the Icelandic sample of admixed origin , because of their disproportionally large effect on their environment.Baseline information of species distribution and their genetic composition is imperative in order to quantify the impacts of climate change on species distribution ranges, biodiversity, and the effects of hybridization between species and populations . Generally, M. edulis was the most common species making up approximately 66% of all sampled individuals. The biogeographic structures of the three Mytilus spp. reflect the major current systems of the region. Pure populations were mainly found in regions (such as W Greenland and the Pechora Sea) with a lower influence of Pacific and Atlantic water, than other sampling sites. Northwards currents from boreal waters facilitate larvae dispersal from southern populations   with M. edulis populations residing in SW Greenland (64°N). This discovery was unexpected, as a seemingly established M. trossulus population has not been found in the high Arctic prior to this study. Several possible mechanisms could explain the presence of M. trossulus in Qaanaaq and Upernavik. First, these populations could have survived in a refugium near NW Greenland during the last glacial period. Glacial refugia are known from North Atlantic temperate regions and evidence suggests that M. edulis may have survived north of the ice margin  further supporting the findings by Brooks and Farmen  suggesting a high degree of isolation between groups. This isolation in turn may have facilitated local adaptation at this rather large geographical scale. For more specific insights on the environmental factors responsible for local adaptation, the geographical scale, and its genomewide significance, a more elaborate sampling design is warranted including more regional samples and a higher degree of genomic coverage.The outlier tests identified six loci as ers Fig.  indicatiers Fig. . Howeverers Fig. . Further4.4Paralithodes camtschaticus and bluefin tuna Thunnus thynnus; CAFF M. galloprovincialis pose an ecological threat to M. trossulus along the Californian coast as it had displaced and continues to displace the native M. trossulus. The surprisingly broad distribution of M. galloprovincialis in the Arctic therefore highlights the benefit of using genetic tools and stresses the need for developing measures to detect and identify nonindigenous species and pathways of introduction, to understand and reduce the threat of invasive species in the Arctic.The effects of global warming increase the spread and associated threat of nonindigenous species across the globe (Gardner et al., Mytilus mussels in the Arctic to be exclusively M. edulis (Berge et al., Mytilus spp. across the Arctic has implications for ecological and ecotoxicological research in the region. Mytilus mussels are extensively used in biological monitoring programs (Wenne et al., Prior to the current investigation, multiple studies have assumed M. trossulus populations with an affinity to the Pacific suggest that exchange of species from the Pacific across the Arctic and into the Atlantic is taking place. However, all of these factors should be further validated through urgently needed studies documenting current distribution and genetic composition of marine species in the Arctic.Moreover, assuming that the distribution and genetic connectivity between regions observed in this study is to be a first approximation representative for benthic invertebrates in general, several important observations were made related to quantifying changes in species distribution in a warmer Arctic. A number of congener species exists, which display different responses to changes in temperature. The genetic connectivity and inferred gene flow are closely linked to major ocean currents, which means that predicting range changes purely based on future climate predictions without considering dispersal potential or barriers can be misleading. In fact, changes in ocean currents and thereby in supply of potential colonizers may be a more important driver of change than warming per se. This has previously been demonstrated by the species changes observed during the large northward expansion of Atlantic water in the Barents Sea and along the W Greenland coast in the 1930s (Drinkwater, http://dx.doi.org/10.5061/dryad.438h3.Data available from the Dryad Digital Repository: The authors declare no conflict of interest. Click here for additional data file.


The appropriate application of genomic technologies in healthcare is surrounded by many concerns. In particular, there is a lack of evidence on what constitutes an optimal genetic service delivery model, which depends on the type of genetic test and healthcare context considered. The present project aims to identify, classify, and evaluate delivery models for the provision of predictive genetic testing in Europe and in selected Anglophone extra-European countries . It also sets out to survey the European public health community’s readiness to incorporate public health genomics into their practice.The project consists of (i) a systematic review of published literature and selected country websites, (ii) structured interviews with health experts on the genetic service delivery models in their respective countries, and (iii) a survey of European Public Health Association (EUPHA) members’ knowledge and attitudes toward genomics applications in clinical practice. The inclusion criteria for the systematic review are that articles be published in the period 2000–2015; be in English or Italian; and be from European countries or from Canada, the USA, Australia, or New Zealand. Additional policy documents will be retrieved from represented countries’ government-affiliated websites. The results of the research will be disseminated through the EUPHA network, the Italian Network for Genomics in Public Health (GENISAP), and seminars and workshops.The transfer of genomic technologies from research to clinical application is influenced not only by several factors inherent to research goals and delivery of healthcare but also by external and commercial interests that may cause the premature introduction of genetic tests in the public and private sectors. Furthermore, current genetic services are delivered without a standardized set of process and outcome measures, which makes the evaluation of healthcare services difficult. The present study will identify and classify delivery models and, subsequently, establish which are appropriate for the provision of predictive genetic testing in Europe by comparing sets of process and outcome measures. In this way, the study will provide a basis for future recommendations to decision makers involved in the financing, delivery, and consumption of genetic services. The past decade has seen the emergence of Public Health Genomics (PHG)—a multidisciplinary field that has established scientific and policy foundations for the appropriate translation of genetic/genomics research into health benefits for individuals and populations . Still, In order to add to the evidence base, the present project, therefore, aims to identify genetic service delivery models for the provision of predictive genetic testing in the European context, and to classify, and evaluate them. The genetic service delivery models will be compared between European and extra-European (Anglophone) countries . The project also aims to assess knowledge and attitudes of European public health (PH) professionals regarding the delivery of genetic services, and to obtain a picture of European PH community’s readiness to incorporate PHG into their practice.For the scope of this project, predictive genetic testing  is defined as the use of genetic testing to predict whether an individual will develop a genetic disease at a later stage of their life; this term is only applicable where the disease-associated mutation is known and highly penetrant .The study will be carried out within the Personalized pREvention of Chronic DIseases (PRECeDI) project (Marie Sklodowska-Curie Research and Innovation Staff Exchange 2014). The PRECeDI consortium is composed of five EU member countries  in collaboration with non-EU project partners . The first task of the consortium was to obtain consensus among the project partners on the most suitable genetic tests that could be employed in the multicenter study. Four genetic tests have been selected during the preliminary meeting that took place in 2015 at Sapienza University of Rome . The selected genetic tests are for hereditary breast and ovarian cancer, Lynch syndrome, familial hypercholesterolemia (as examples of genetic tests of proven effectiveness and cost-effectiveness) , 7. The (i)practice setting and financial resources (public vs. private);(ii)service provider and patient access [geneticists vs. primary care physicians/other medical specialists ];(iii)policy regulation ;(iv)laboratory practice standards ;(v)information dissemination (methods of providing information about genetic services to patients and service providers).There are a number of factors unique to each genetic service provision, which could be used to categorize genetic service delivery models. These factors have been summarized in 10 questions formulated by the USA Genetic Service Policy Project (GSPP) Report   of translation research in genomic medicine [where “translation” is defined as “the sequence of events in which a proven scientific discovery is successfully integrated into established practice and policy” ], namelyThe present project will, therefore, take all these factors related to genetic services into account in order to identify, classify, and evaluate genetic service delivery models for predictive genetic testing present in European countries and in selected extra-European (Anglophone) countries.The project will be carried out through a multidimensional approach, which includes (i) a preliminary (non-systematic) literature search to define genetic services and genetic delivery models; (ii) a systematic review of published literature on existing genetic service delivery models and selected country websites for policy documents; (iii) structured interviews with health experts on genetic service delivery models, policies governing the use of genomics medicine, and evaluation of genetic testing and related services in their respective countries; and (iv) a survey of European Public Health Association (EUPHA) members’ knowledge and attitudes regarding the use of genomic applications in clinical practice.Although the terms “genetic(s) service(s)” and “genetic delivery models” appear frequently in the peer-reviewed literature and in documents on genetics policy-related websites, they are usually not defined. Therefore, a preliminary (non-systematic) literature search was carried out to define the two terms. A common search strategy was used to identify articles from three electronic databases  with the following keywords: genetic(s) service, medical genetics, genetic service delivery, genetic(s) service delivery model, and genomic service delivery. Only articles defining the two terms “genetic(s) service(s)” and “genetic delivery models,” describing or classifying genetic service delivery models and published in English or Italian languages were included. No period restrictions were applied.–relevant articles and reports on pilot studies, best practices, and funded projects inherent to genetic service delivery;–genetic services concerning the delivery of all types of genetic tests;–genetic services for predictive genetic testing provided by genetic specialist teams, and healthcare professionals practicing in primary or secondary care;–publication year between 2000 and 2015;–studies published in English and Italian languages;–interventions carried out in European and extra-European countries .The systematic review focusing on existing genetic service delivery models will be performed according to the PRISMA Statement . The seaThe present project will focus on genetic service delivery models in Europe; therefore, other geographical areas considered will be used only for comparison.–studies reporting only on genetic counseling services;–descriptive studies where a specific delivery model cannot be identified;–studies not specifying the type of genetic test offered.The exclusion criteria will be:Specific websites on PHG of EU countries  and extra-European countries  will be consulted as an additional resource to identify policy documents on delivery models .(a)identify any genetic services delivery model that was not identified through the literature search;(b)enhance the collection of process and outcome indicators used for quality assessment of genetic services delivery models;(c)collect opinions of expert panels on the genetic services delivery models in their countries, in terms of strengths and weaknesses—that are also barriers and facilitating factors for the genetic model implementation—and possible improvements of the models.Experts’ interviews will be conducted through an online questionnaire to:Prior to the survey, a National Reference Group (NRG) will be established in each EU member state to select experts with different backgrounds and supervise the study at the national level. The panel of experts will have the following characteristics: (a) good knowledge or practical experience of at least one of the four types of selected genetic tests and (b) representative of each included country . The final number of experts will depend on the different contexts of each country.Demographic and professional information;Genetic services delivery models for BRCA1/2, Lynch syndrome, familial thrombophilia, and familial hypercholesterolemia genetic testing.The first part of the survey will focus on four types of genetic test . This part of the survey addresses healthcare professionals  working in genetic services with manager roles or in direct contact with patients requiring one of the four genetic tests. The NRG will select at least five experts for each genetic test to reach a minimum of 20 experts in each country. Stand-alone questionnaires are being developed for each genetic test with the following sections:Demographic and professional information;Evaluation of genetic services activity;Evaluation of quality of genetic services;Evaluation of health outcomes;Electronic records and genetic information;Coverage of genetic services in the country.The second part of the survey addresses health information management professionals who deal with health data collection and analysis at local , regional , or national level . The aim is to describe the flow and management of health information from each health facility to regional and national agencies where aggregate data are produced and used for planning activities. The NRG will select a minimum of five experts in each country. The related questionnaire will be composed of six sections:Demographic and professional information;Policy issues;Genetic services: access and availability;Professional education and training.The third part of the survey addresses experts in policy planning and policy research of genetic services employed in national institutes , universities or clinical research centers and it will focus on policy of genetic testing and related services. The NRG will select at least five experts in each European country. The questionnaire will be composed of the following sections:Once the selection process is completed, a link to the final version of the online questionnaire will be e-mailed to the participants. They will be given a time frame of 6 months to participate in the survey. Up to two reminder e-mails will be sent to non-responders 3 and 5 months after the initial e-mail to increase the response rate.Public health professionals may play different roles in the translation of genome-based knowledge and technologies into PH. They may use genomics tools to evaluate the health impact of PH interventions on different subsets of the population . DespitePersonal details;Professional activity;Knowledge of genetic testing and delivery of genetic services;Attitudes on genetic testing and the delivery of genetic services;Attitudes regarding the roles of PH professionals in PHG.Looking ahead to the incorporation of PHG into PH practice in Europe, a similar survey will be conducted in a sample of European PH professionals, members of EUPHA. EUPHA is the umbrella organization for PH associations and institutes in Europe. It is composed of 71 member organizations from 41 countries and has about 5.900 individual members. The online survey will be carried out in order to obtain a picture of the European PH community readiness to incorporate PHG in their practice. The survey will focus on attitudes and knowledge of PH professionals toward genomic applications in clinical practice, the delivery of genetic services, evaluation of genetic service delivery models, and the role of PH professionals in the implementation of PHG. The questionnaire will be composed of the following five sections:A link to the final version of the online questionnaire will be e-mailed to the 5.900 EUPHA members. The individual members could fit one of the following categories: (a) PH professionals involved in PHG; (b) PH professionals not involved in PHG; (c) not PH professionals involved in PHG ; (d) not PH professionals not involved in PHG . A filter question will direct professionals not involved in PHG activities to a reduced version of the questionnaire, comprised of only four items in sections C and D.Participants will be given a time frame of 6 months to participate in the survey. To increase the response rate, up to two reminder e-mails will be sent to non-responders 3 and 5 months after the initial e-mail. In case the response rate should not be sufficient, hard copies of the study will also be distributed to the participants during a EUPHA Conference. A pilot phase will be conducted prior to administration of the questionnaire to EUPHA members in order to ensure practicability, validity, and correct interpretation of results.–General description of the study and the genetic service. This section collects general information about the study  and the genetic service ;–Information on patients and pathways to care. This section investigates the characteristics of the target population of the genetic service and pathways to care, as well as cost-effectiveness and efficacy of the genetic service;–Genetic service evaluation. This section investigates the type of genetic service delivery model, strengths, and weaknesses of the model, as well as the genetic service capacity in terms of population and geographic area served, staff qualification, laboratory characteristics, and outcome evaluation.Data from the literature review and surveys will be collected and analyzed by the authors. A data extraction form has been developed specifically to collect relevant information from the studies included in the systematic review  and is composed of three parts:Five members of the working group made an independent evaluation of each genetic service using the data extraction form, followed by extensive group discussions. Eventual discrepancies were resolved after discussion with the coordinators of the project. The coordinators were responsible for revising and standardizing the preliminary results and for supporting the working group throughout the whole evaluation process.In the experts’ interview, the diffusion of each genetic service delivery model in each country will be assessed through a three-point Likert scale , while the likelihood that a specific genetic services pathway is associated with one of the identified delivery models will be assessed by another three-point Likert scale .In the EUPHA survey, attitudes of PH professionals will be assessed through a three-point Likert scale , while knowledge will be assessed through a combination of multiple choice questions and three-point Likert scale answers.Internal consistency of all questionnaires will be assessed by obtaining Cronbach’s alpha coefficients.The final results of the project will be available in 2019 and will be disseminated through the EUPHA network, the Italian Network for Genomics in Public Health (GENISAP), seminars and workshops. In particular, internal workshops and open seminars have been scheduled for the period 2016–2018.The preliminary literature search produced eight records useful in defining the terms “genetic(s) service(s)” and “genetic delivery models” and in identifying the wide range of genetic services provision , 18–25. broad context within the PHG framework in which genetic services are offered to individuals and families with or at risk of genetic disorders. In other words, a genetic delivery model is a combination of personal healthcare services provided by healthcare professionals to individuals and families  and PH services and functions .Particularly useful in defining the term “genetic delivery models” were the 10 questions of the GSPP Report , which s(i)multidisciplinary specialist clinics and coordinated services in rare genetic disorders led by geneticists;(ii)genetic services integrated in other medical specialties ;(iii)genetic services integrated into primary care;(iv)genetic services provided in screening programs .The two articles by Gu et al. , 23 and The classification by Battista et al.  centers (i)The Patient–Doctor–Counselor Model;(ii)The Patient–Doctor–Lab Model;(iii)The Patient–Counselor–Lab Model; and(iv)The Patient–Lab  Model .The classification provided by Gu et al. , 23 instThe final classification of genetic services delivery models will take into consideration the delivery models described by Battista et al.  and all The process and outcome indicators collected from the present project will be used to define a minimum set of indicators necessary for the assessment of genetic services through a consensus procedure among the partners of the PRECeDI project .With regard to knowledge and attitudes of PH professional, we can anticipate that poor knowledge of genetics will be a barrier to the provision of genetic services . It will surely interfere with the process of incorporating genetics into clinical practice.Results of this project may be disseminated in scholarly articles and at academic conferences but no personal information about the participants will be used in the reports or manuscripts.The transfer of genomic technologies from research to clinical application is influenced not only by several factors inherent to research goals and delivery of healthcare but also by external and commercial interests that may cause the premature introduction of genetic tests in the public or private sector . Furthermore, current genetic services are delivered without a standardized set of process and outcome measures, which are essential for the evaluation of healthcare services. It is important that only genetic/genomic applications with proven efficacy and effectiveness are delivered to populations, and particularly that technologies have favorable cost-effectiveness ratios . This stIn conclusion, the current project will identify possible points of improvement for currently implemented genetic services delivery models in Europe and provide recommendations to decision makers involved in the financing, delivery, and consumption of genetic services.The project is carried out in accordance with the Italian data protection code for sensitive data (Legislative Decree no. 196/2003) and informed consent will be obtained through an online consent form in accordance with the Declaration of Helsinki. The protocol has been submitted to the Ethics Committee of Sapienza University of Rome, Italy.All authors contributed to the conception and design, and are currently carrying out the study. BU, TL, and PV wrote the present manuscript. All authors read and approved the final manuscript.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.


Taken together, our results suggest that targeting acetyl-STAT3 (K685) provides potential therapeutic opportunity to treat a subset of human cancers.Epigenetic regulation of gene expression is an emerging target to treat several human diseases including cancers. In cancers, expressions of many tumor suppressor genes are suppressed by hyper-methylation in their regulatory regions. Herein, we describe a novel carbazole SH-I-14 that decreased the level of the acetyl-STAT3 at the K685 residue. Mutation analysis revealed that SH-I-14 disrupted STAT3-DNMT1 interaction by removing acetyl group from K685 of STAT3. Finally, the inhibition of STAT3-DNMT1 interaction by SH-I-14 resulted in re-expression of tumor suppressor genes such as VHL and PDLIM4 through de-methylation of their promoter regions. In addition, SH-I-14 showed anti-proliferative effect in triple-negative breast cancer (TNBC) cell lines  Signal transducer and activator of transcription 3 (STAT3), a member of STAT family, is a transcriptional regulator that mediates transduction of extracellular signals to the nucleus in response to various cytokines . STAT3 iThe regulation of STAT3 activity through reduction of phosphorylation , 4 and v9H-carbazole was first described in 1872 .Animal use procedures were approved by the Institutional Animal Care and Use Committees of Georgetown University Medical Center. MDA-MB-231 cells  or DMSO was administered into peritoneal cavity of mouse daily for 5 days. Mice were euthanized at 1 hr after last administration of drug. Tumors from each mouse were lysed and subjected to western blot analysis.P < 0.05; ** indicates P < 0.01; and *** indicates P < 0.001.To compare two groups of interest, the Turkey’s multiple comparison test (ANOVA) was applied for statistical analysis. * indicates


Anopheles darlingi, from a microgeographical perspective.In recent decades, throughout the Amazon Basin, landscape modification contributing to profound ecological change has proceeded at an unprecedented rate. Deforestation that accompanies human activities can significantly change aspects of anopheline biology, though this may be site-specific. Such local changes in anopheline biology could have a great impact on malaria transmission. The aim of this study was to investigate population genetics of the main malaria vector in Brazil, Microsatellites and ddRADseq-derived single nucleotide polymorphisms (SNPs) were used to assess levels of population genetic structuring among mosquito populations from two ecologically distinctive agricultural settlements (~60 km apart) and a population from a distant (~700 km) urban setting in the western Amazon region of Brazil.Anopheles darlingi populations via both model- and non-model-based analysis only with the SNP dataset. Microsatellites detected moderate differentiation at the greatest distances, but were unable to differentiate populations from the two agricultural settlements. Both markers showed low polymorphism levels in the most human impacted sites.Significant microgeographical population differentiation was observed among Anopheles darlingi, possibly related to local environmental anthropic modification. This divergence was observed only when using high coverage SNP markers.At a microgeographical scale, signatures of genetic heterogeneity and population divergence were evident in The online version of this article (doi:10.1186/s13071-017-2014-y) contains supplementary material, which is available to authorized users. Plasmodium [Anopheles darlingi is the primary vector. Four main factors of An. darlingi’s life history have contributed to its pivotal role in Plasmodium transmission: susceptibility to human Plasmodium species; anthropophilic or opportunistic behavior [The prevalence of malaria in tropical and subtropical regions  is due masmodium . Among Nasmodium  where Anbehavior –5; rapidbehavior , 7; and behavior , 9.An. darlingi population structure spatially [An. darlingi and the highest proportion of malaria cases compared with older settlements where there is increased deforestation and urbanization, and fewer malaria cases, a phenomenon described as frontier malaria [An. darlingi populations from three endemic areas, ranging from a rural to an urban environment. Different proportions of anthropogenic (built) environment between urban and rural settings may lead to ecological segregation in breeding sites, resulting in divergence/speciation, as observed in An. gambiae (s.l.) in Cameroon [Deforestation and microclimate change that accompany human activity can significantly increase the human biting rate and other vector biology parameters in anopheline vectors across the globe , 10, 11,patially , 17, 18 patially , 20. In  malaria , 22. In Cameroon .An. darlingi and other vector species [An. darlingi, microsatellite markers have revealed moderate to high levels of genetic heterogeneity; subpopulations have been found at a macrogeographical scale (greater than 150 km apart) [An. darlingi by supporting the existence of three genetic clusters (putative species) within this vector in Brazil at a large scale [An. darlingi populations at a fine geographical scale in a heterogeneous landscape such as the Amazon region. Here, we inferred genetic divergence in An. darlingi populations at a local scale.Population genetic studies in the context of vector biology have used a variety of molecular markers, among them microsatellites and single nucleotide polymorphisms (SNPs). The former is a multiallelic marker that provides valuable polymorphism information, and it has been an important tool for numerous population genetics studies in  species –26. In Am apart) , 27, 28,m apart) . Single m apart) , 30. Resm apart) , 32. Forge scale . This stge scale , 35, butAn. darlingi and stored at -20 °C  in two rural settlements, Granada and Remansinho in March 2012. Outdoor samples from the urban site of Cruzeiro do Sul were collected in March 2013  previously described [HE), allele richness (Rs), and private allele (P) were performed in FSTAT v 2.9.3.2 [DNA was prepared from each mosquito with 5% Chelex solution . Nine microsatellite loci were genotyped for 175 escribed , 27. Ampescribed . Estimat 2.9.3.2 .An. darlingi specimens (see Table Anopheles darlingi in Brazil [EcoRI-MspI restriction enzymes was performed in a 40 ul reaction volume and then purified with AMPure XP beads following the manufacturer’s protocol. A pair of customized adapters (P1 and P2) were designed including Nextera® Index Primers  complement sequence, to perform the indexing with Nextera® DNA Sample Preparation Kit (Illumina)  for each RAD locus, which passed through a minimum allele sequence depth of 5, as used by Emerson and collaborators [Stacks v1.31  pipelinee genome  using Boe genome , and staborators , that waK value (ranging from 1–4) using a 100,000 ‘burn-in’ period and 1,000,000 generations. The optimal value of K was inferred using the Evanno method [FST estimates of genetic diversity, as well as Hardy-Weinberg (HW) equilibrium tests and linkage disequilibrium (LD) between pairs of microsatellite loci were computed using ARLEQUIN 3.5 [α = 0.05; when multiple tests were performed, the sequential Bonferroni procedure was applied. In addition, as microsatellites are known to give precise, but often downwardly biased estimates of genetic differentiation [GST (G"ST) [A Bayesian clustering analysis with STRUCTURE  was perfo method  implemeno method . Locus-sQUIN 3.5 . The nomntiation , we incl (G"ST) , using G (G"ST) , that st (G"ST)  in R sof (G"ST)  was usedHE, Fis and allelic richness (Rs) per locality and sampling period are presented in Additional file Rs) and number of private alleles (P) were observed in Remansinho  to 0.133 (P < 0.0001) , around 46 million sequences passed several levels of quality filtering in the process_radtags program , which were assigned to each collection point  than with microsatellites G"ST = 0.119, 0.065–0.219 (2.5–97.5% CI), but the values were not so different as in FST estimates.Overall diversity was also calculated using FST estimation, and non-model-based analysis by DAPC. BA assumes a model-clustering method based on allele frequencies at each locus, and probabilistically each individual is assigned to a number of genetically distinct clusters (K) [FST estimates between Cruzeiro do Sul and the two rural settlements than between the two rural settlements, however the estimates based on SNPs were more than 4-fold higher than those based on microsatellites between Cruzeiro do Sul and rural settlements, and 35-fold higher between Granada and Remansinho  with STRUCTURE, ters (K) . In the ho Table .High-throughput methods using next generation sequencing that analyze a subsample of the genome, such as ddRADseq, have two major advantages compared to microsatellites, the need of smaller sample sizes and also no need of prior knowledge of the genomic sequence . In the PCA of the SNP data separates individuals originating in Cruzeiro do Sul from those in Granada and Remansinho (separated by ~ 700 km) along the first principal component that explains 19.5% of the variation Fig. . NonethePlasmodium and little effective shelter from bites of infected An. darlingi. Proximity of residences to potential mosquito breeding-sites is also associated with the likelihood of becoming infected with Plasmodium [An. darlingi support the hypothesis that deforestation may be associated with a loss of genetic diversity [An. gambiae in the western Kenyan highlands [An. darlingi in settlements that are at different temporal points in the frontier malaria model. Once roads have been built for settlements, deforestation to clear space for housing and crop planting is a priority.Rural settlements are in constant flux due to human interventions such as agricultural development, forest degradation, and increased and often mobile human populations , 55. Sucasmodium –59. The asmodium . Regardlasmodium . Our finiversity , 62. Defighlands , 64. A sSmall-area interventions may be an effective approach for malaria control and elimination in the neotropics and globally, once transmission pockets have been identified and characterized –67. Each.In this study, we provide evidence that the detection of microgeographical population structure at a fine scale is only robust when we apply high-resolution molecular typing techniques, since conventional approaches based on microsatellite markers may underestimate overall genetic distances in closely related vector populations. In our view the application of ddRADtag sequencing for genetic analysis of mosquito populations represents a suitable molecular tool to further elucidate vector population dynamics in malaria endemic areas