Varroa genus is known for a lineage of Varroa destructor that shifted to the Western honey bee, Apis mellifera, with disastrous effects on wild populations and the beekeeping industry. Despite this, the biology of Varroa spp. remains poorly understood in its native distribution range, where it naturally parasitizes the Eastern honey bee, Apis cerana. Here, we combined mitochondrial and nuclear DNA analyses with the assessment of mite reproduction to determine the population structure and host specificity of V. destructor and Varroa jacobsonii in Thailand, where both hosts and several Varroa species and haplotypes are sympatric. Our data confirm previously described mite haplogroups, and show three novel haplotypes. Multiple infestations of single host colonies by both mite species and introgression of alleles between V. destructor and V. jacobsonii suggest that hybridization occurs between the two species. Our results indicate that host specificity and population genetic structure in the genus Varroa is more labile than previously thought. The ability of the host shifted V. destructor haplotype to spillback to A. cerana and to hybridize with V. jacobsonii could threaten honey bee populations of Asia and beyond.Host shifts of parasites are often causing devastating effects in the new hosts. The  Surveying the distribution of mitochondrial haplotypes in the same regions as Warrit et al. ; (2) Bang Saen  with V. jacobsonii haplotype North Thai; (3) Ko Samui (island) with V. jacobsonii Samui; (4) Phattalung (South) with V. jacobsonii Malay  and were therefore not screened in this region.Between 2013 and 2015, 200 Thailand , Fig. 1:ang Saen , Fig. 1.et al., Upon opening of infested host brood cells, the reproductive state of mite foundresses was determined . For the latter, the tubes were heated at 65 °C for 30 min and then at 100 °C for 10 min before adding 40 µL double distilled H20. The tubes were then vortexed and centrifuged. Ten microlitres of 2X GenStar PCR-ready mix (with Taq + loading dye), 7 µL double distilled H20, 1 µL forward, 1 µL reverse primers and 1 µL of DNA extract was added to PCR tubes. Total DNA of mites collected in Bang Saen (n = 51) was isolated according to Beaurepaire et al. (N = 164) were extracted with Chelex: the ethanol used to preserve the mites was rinsed twice in double distilled H2O and each mite was placed individually in 100 µL 5% Chelex solution in a 96 well plate and crushed with a pestle. Finally, 5 µL proteinase K were added and the plate was placed in a thermocycler with standard Chelex cycling conditions  and Taq polymerase (0.63 units) were mixed in 25 µL final reaction volume. Primers given in Table S1 were used to produce 380 and 800 bp amplicons.PCR assays were performed to amplify regions of the cytochrome oxidase subunit I (cox1) gene of the mites sampled from the North, South and island locations  following the manufacturer's recommendations. Purified PCR products were commercially sequenced. Each PCR product was sequenced in both directions.The PCR cycling protocols are given in Table S2. The PCR products were analysed with a 2% two-dimensional agarose gel electrophoresis. The gels were stained GelRed  for visualization under UV light. The PCR products were purified using the NucleoSpinet al., et al., http://popart.otago.ac.nz).A dataset including the overlapping region of the 380 and 800 bp sequences together with GenBank references , an analysis not relying on a priori information was conducted with the software InStruct  varied from 1 to 12 and 20 chains for each run were performed with 50 000 burn-in iterations and 100 000 total iterations for each chain using the Admixture model. The most likely number of clusters was then estimated manually following the method described in Evanno et al. , allelic richness (R) and the expected (He) and observed heterozygosity (Ho) indexes were then calculated for each mite group sampling location using the software Fstat V. 2.9.3  were calculated using GenAlex V. 6.503  was conducted on the same dataset to identify the main genetic clusters among the mite samples. Since we were interested in the occurrence of putative hybrids, we performed the PCA including the data of both species. The R package Adegenet Jombart,  in R v. A. mellifera colonies in North Thailand (N = 118) were identified as the V. destructor Korean haplotype 1 (K1) (N = 89) either had not reproduced or were collected from early host brood stages on which reproduction is not yet detectable. The exception was a non-reproductive V. jacobsonii mite in an A. mellifera colony   and 3. Ta colony . This inVarroa destructor K1 mites were also found in two years in ten drone brood cells of four A. cerana colonies in the North  or of the China haplotype 2 . Each of these mite species and haplotypes reproduced on drone brood in at least one occurrence in these four colonies.MtDNA genotyping showed that four aneously . One of s.d., Table S4). The average allelic richness per locus varied from 2.1 to 6.4 . With the exception of low values for V. jacobsonii Samui2, the two genetic diversity parameters were inferior by a factor 2 in V. destructor compared to V. jacobsonii , none of the populations sampled were at a Hardy–Weinberg equilibrium. Notably, Ho was higher by a factor 2 in V. jacobsonii than in V. destructor, again with the exception of V. jacobsonii Samui2 . These markers were polymorphic, with a range of 3–16 alleles per locus . Plotting the individuals belonging to the two genetic clusters revealed a strong host specificity at most locations (N = 5 in A. cerana and N = 1 in A. mellifera) were detected in the North of the country  and that mites sampled in A. cerana colonies shared >98.90% identity with V. jacobsonii .The analysis of population structure using InStruct showed that the most likely number of clusters in our dataset is ocations . However country . Since aA. cerana in the North (N = 1) and the South (N = 1) and in both hosts in the centre  were found in V. jacobsonii and V. destructor, along the axis 1, which separated the species, and which explained 30% of the genetic variance (V. destructor populations. Factor 3 (7% of the variance) did not separate V. jacobsonii from the North and the centre of Thailand, but these two populations were separated from the island and the South populations on the third axis  showed strong significant differences between the mites parasitizing the two host species in the northern and central locations . In mites infesting A. cerana, the population differentiation estimates were highest when comparing the continental populations  to the island population , and among locations for mites infesting A. mellifera (60.9%).The AMOVA results indicated that genetic differences among mites infesting colonies of the same location were the least important in Varroa spp. haplogroups detected previously , South  and on Samui Island, respectively.All haplogroups reported earlier  infesting A. cerana outside its original distribution range , suggests that opportunities for host shifts by this mite species  supports the idea that opportunities for hybridization can indeed be frequent.Drifting of mites between host species, as well as the natural sympatry of several haplotypes of mites, can lead to infestations of single host colonies and even brood cells by mites of multiple haplotypes and species, thereby setting the stage for hybridization. Indeed, such cases were detected in five et al., V. destructor genotype and 99.88% identity to the K1 COI haplotype (Tables S7 and S8). The closest allele found in the gene pool of V. destructor is 165 . With a repeat motif of this microsatellite of 2 bp, at least five additions/deletions would be necessary to generate homoplasy, which seem highly unlikely.The occurrence of several species and haplotypes in single colonies leads to the possibility of foundress mites of different taxa entering the same host brood cell to reproduce  population, which showed the high range in allelic richness typical for V. jacobsonii (except Samui2), but a lower range of heterozygosity  indicates that the sampled V. destructor and V. jacobsonii was overall low (Table S5) but may be mediated by occasional hybridization. The comparison of the different indexes of population differentiation revealed contrasting patterns in the mites infesting the two host species. The two indexes FST and GST were generally higher in A. mellifera than Dest. This trend was reversed for the mite populations infesting A. cerana. These discrepancies can be explained by the differences in the number of alleles and heterozygosity levels within these two groups . In contrast, the moderate genetic variance at this level in V. destructor reflects the lack of diversity of the Korea haplotype outside its natural distribution (Solignac et al., Varroa population structure, varying in space, time and according to its host species, a broader sampling scheme will be necessary to seize the extent of this parasite's complex biogeography in Asia.Additionally, we detected a low genetic structuration among colonies of the same location in A. cerana and A. mellifera by V. jacobsonii and V. destructor. Genetic diversity of V. jacobsonii was higher compared to V. destructor. Spillbacks of invasive V. destructor mites from A. mellifera into A. cerana and spillovers of endemic V. jacobsonii mites from A. cerana to introduced A. mellifera were observed. These events resulted in infestations of single colonies with both mite species and microsatellite marker based evidence suggested hybridization between V. destructor and V. jacobsonii. The relatively high frequency of these phenomena indicate risks of further host shifts, which could threaten honey bee populations of Asia and beyond.Several of the phenomena known to promote host shifts have been observed in our screening of natural infestations of


Is it possible to predict the freely chosen content of voluntary imagery from prior neural signals? Here we show that the content and strength of future voluntary imagery can be decoded from activity patterns in visual and frontal areas well before participants engage in voluntary imagery. Participants freely chose which of two images to imagine. Using functional magnetic resonance (fMRI) and multi-voxel pattern analysis, we decoded imagery content as far as 11 seconds before the voluntary decision, in visual, frontal and subcortical areas. Decoding in visual areas in addition to perception-imagery generalization suggested that predictive patterns correspond to visual representations. Importantly, activity patterns in the primary visual cortex (V1) from before the decision, predicted future imagery vividness. Our results suggest that the contents and strength of mental imagery are influenced by sensory-like neural representations that emerge spontaneously before volition. Sometimes, thoughts feel spontaneous and even surprising; while other times they feel effortful, controlled and goal oriented. When we decide to think about something, how much of that thought is biased by pre-existent neural activity? Mental imagery, a sensory thought, can be triggered voluntarily or involuntarily4. However, how much of the content and strength of our mental images we actually control when we voluntarily generate imagery remains unknown. For example, individuals with post-traumatic stress disorder (PTSD) report a complete lack of control of both the content and strength of their mental imagery5. While evidence suggests that imagery strength varies both between and within individuals in the normal population6. Previous research has shown that prefrontal activity can predict future decisions10, and nonconscious sensory activity11, and that mental images can be decoded from early visual cortex13. However, it remains unknown whether nonconscious sensory activity influences what we think and how strongly we think it.A large amount of psychology and, more recently, neuroscience has been dedicated to examining the origins, dynamics and categories of thoughts16. Additionally, in an independent control experiment, we estimated the temporal reliability of the reported onset of thoughts, as it has been criticized in previous paradigms17. Using a design exploiting the known effect of imagery priming on subsequent binocular rivalry as a function of time18, we show that participants’ reports of thought onsets were indeed reliable within the temporal resolution of fMRI.To investigate the origins of the content and strength of voluntary imagery, we crafted a thought-based mental imagery decision task, in which individuals could freely decide what to imagine, while we recorded brain activation using functional magnetic resonance imaging (fMRI). We used multi-voxel pattern analysis  to decode information contained in spatial patterns of brain activation recorded using fMRI19. In addition to the executive areas involvement in future visual thoughts, we aimed to test whether predictive information could also be decoded from visual areas, as previous results have shown that visual imagery recruits visual areas13. To test this, we used both searchlight and visual (from V1 to V4) regions-of-interest (ROI) decoding. We also sought to determine the representational content of the predictive signals: is predictive information, to some extent, similar to perceptual visual representations? To assess this, we perceptually presented gratings outside of attention to participants in separate runs. Functional brain images from the perceptual blocks were then used to train classifiers, which were subsequently tested on imagery blocks both before and after the decision. This so called perception-imagery generalization cross decoding was thus used to show common informational content between visual perceptual representations and predictive signals. Finally, we tested whether the subjective strength of visual imagery could be decoded from information in visual areas before reported volition. Such an involvement of visual areas in the future strength of visual imagery would provide further evidence that sensory areas also play an important role in the phenomenology of future thoughts.Models of determinants of decision making postulate that executive areas in the prefrontal cortex would trigger selection processes leading to future choicesUsing this paradigm, we found that activity patterns were predictive of mental imagery content as far back as 11 seconds before the voluntary decision of what to imagine –in visual, frontal and subcortical areas. Importantly, predictive patterns in the primary visual cortex (V1) and the lateral prefrontal cortex were similar to perceptual representations elicited by unattended images. We show that the subjective strength (vividness) of future mental imagery can be predicted from activation patterns contained in the primary visual cortex (V1) before a decision is made. Our results suggest that the contents and strength of mental imagery are influenced by sensory-like neural representations that emerge spontaneously before volition. These results are important as they point to a role of visual areas in the pre-volitional processes leading to visual thought production, thus shedding light on the mechanisms of intrusive mental imagery in conditions such as PTSD, as well as the origins of normal mental imagery.21. Participants chose to imagine each grating with similar probabilities .Our paradigm consisted of a mental decision leading to the formation of a visual mental image. In every trial, participants had to choose to imagine one of two possible different colored and oriented gratings while we recorded brain blood-oxygen-level dependent (BOLD) using fMRI Fig. . On aver−8, 1.2·10−9, 7·10−11 and 1.5·10−3; from V1 to V4) and imagery . These results are comparable to previous results on decoding perception and imagery24 and thus validate our decoding approach.We first verified the suitability of our decoding approach to classify the contents of visual perception and imagery. We used SVM classifiers trained and tested  on 10 s of perception or imagery data and classified the perceptual or imagined stimuli  in visual areas from V1 to V4 . Fig. 16. We used two sources of information to decode the contents of imagery: neural activation patterns within the imagery condition (imagery decoding) and patterns from unattended perceptual stimuli to decode imagery data . For the imagery decoding, we trained and tested classifiers using the imagery data. In the imagery-perception generalization analysis we trained the classifiers using data from the perception scans and tested on imagery data. The latter allowed us to explore shared information between perception and imagery, without the effects of attention .To investigate which brain areas contained information about the contents of imagery, we employed a searchlight decoding analysis on fMRI data from the whole brainWe defined the areas bearing information about the contents of imagery as those revealing above chance decoding accuracy at any point in time during a 28 s time window around the decision . Under this selection criterion, above chance decoding at any point in time is trivial and not relevant for our question. Rather, the purpose of this analysis is investigating the temporal dynamics of the imagery-content information. Specifically, we were interested to test whether any area contained information about the contents of imagery before the decision. In this respect, our analysis is bias-free regarding the temporal position of the information, as we considered many time-points before and after the decision (7 points each).25. Time-resolved classification in the imagery condition reached above chance decoding accuracy up to 11 seconds before reported imagery onset in occipital and thalamus while significant classification was reached at −9 seconds in the pons . Previous studies have shown that prior decisions can impair subsequent cognitive tasks27. Therefore, the cognitive load for the decision element of our task could impair imagery, which is consistent with the results of a behavioral control experiment showing that cued imagery (no-decision) was stronger than decision followed by imagery  and −3 seconds in frontal areas , indicating that this behavioral task can resolve differences in priming spaced by 3.33 seconds, at least for these two first time points, thus providing a lower bound of temporal resolution of the accuracy of the reported imagery onset which is comparable to that of fMRI.We ran an independent behavioral experiment outside the scanner to test whether participants might have begun imagining before they reported having done so, which could explain early above chance classification. We utilized a method that exploits binocular rivalry to objectively measure imagery strengthion Fig. . We reas−5, Fig. 17.Figure 29 . Permutation tests yielded similar results to those using parametric tests  and tested on the subsequent trial . If there was spill over from the previous trial, this analysis should show similar or higher decoding accuracy in the pre-imagery period. We found no significant above chance classification for any of the regions, thus ruling out the possibility that these results are explained by any spill over Fig. .Results from the searchlight analysis were inconclusive regarding whether the predictive information before the decision share similarities with visual perception, as only frontal areas exhibited robust perception-imagery generalization decoding Fig. . To testThe imagery ROI decoding analysis revealed similar temporal dynamics to the searchlight approach, showing earliest above-chance decoding accuracy −11 seconds from the reported imagery decision in the primary visual cortex, V1 Fig. . In the 31. This discrepancy with previous results could be due to experimental noise or to a lack of representational similarity between perception and imagery. To distinguish between these two alternatives, we performed a new analysis seeking more sensitivity by abandoning the time-resolved analysis as described in the next section.The perception-imagery generalization showed more modest effects with above chance decoding accuracy in V3 just 3 s before imagery onset . As expected, the decoding accuracy for imagery content was higher in high-vividness trials, but surprisingly, the strongest differences were observed before the onset of imagery Fig. . The genFinally, we reasoned that if prior, pre-imagery sensory representations in early visual cortex do indeed dictate the strength of subsequent visual imagery, then the pre-imagery data should predict the reported vividness from the subsequent imagery period. Accordingly, we tested exactly this, we attempted to decode the subjective strength of imagery (i.e. vividness) by using only the fMRI data from before the imagery period Fig. . DecodinWe found that neural activation patterns were predictive of the contents of voluntary visual imagery as far as −11 seconds before the choice of what to imagine. These results suggest that the contents of future visual imagery can be biased by current or prior neural representations.33, we remain agnostic as to whether predictive signals were accompanied by awareness or not. We acknowledge the inherent limitations of most paradigms at capturing the state of awareness of the participants before their decision (see for example17). We have nonetheless gone to great lengths to overcome these limitations by developing a behavioral test aimed at probing the accuracy of imagery onset reports  and also on abstract decisions (up to 4 seconds10). Crucially, questions have been raised about whether the decoding of such signals can correspond to neural activity elicited by the preceding trial. The N-1 trial shifting or “spillover” analysis performed in our study . Results of the spillover control analysis showed that the predictive signals in our study are not explained by the previous trial, thus dismissing spillover effects as an explanation of our data  the probability of switching gratings from one trial to the next deviated from chance (58.59%). Therefore, by taking the results from the imagery decoding alone, we cannot rule out that sequential dependencies could have influenced the classification, as the classifier would have reached 58.59% decoding accuracy just by predicting that the decision on next trial would be switched from the previous one. Crucially, our independent perception-imagery generalization decoding analysis does not suffer from sequential dependencies issues as classifiers were trained exclusively on perception trials (presented in a 15s-on/15s-off block design) and tested on imagery trials. The perception-imagery generalization decoding confirmed predictive signals before the decision from  could be potentially exploited by the classifier. Previous studies have shown that classifiers trained only on behavioral responses can perform as well as or better than classification on neural responsesrom Figs , thus inInterestingly, information contained in the primary visual cortex (V1) predicted the subjective strength of visual imagery Fig. . This su9. Thus, it could be possible to interpret our results as the imagery decision being made (at least partly) non-consciously, supporting the idea that subjective sensation of making the decision emerges after the decision is already made33.In previous experiments applying MVPA to study decision processes, predictive information about choices has been interpreted as evidence for nonconscious decision making37.An alternative hypothesis is that these results reflect decisional mechanisms that rely on spontaneously generated visual representations present before the decision. Since the goal of the task was to randomly choose and imagine a grating as vividly as possible, one strategy might be to choose the pattern that is spontaneously more strongly represented. In other words, spontaneous grating representations might stochastically fluctuate in strength while remaining weak compared to voluntary imagery. Thus, prior to the decision, one grating representation might dominate, hence being more prone to decisional thought-selection. An analogous interpretation has been advanced to explain the buildup of neural activity prior to self-initiated movements, aka readiness potential38, suggesting that the decision can be somewhat dissociated from predictive neural signals. Therefore, our results can be explained by a conscious choice that relies on weak neural representations during the decision production; perhaps analogous to blindsight39, subliminal priming studies41 or nonconscious decisional accumulation42. Such a mechanism is intriguing in light of theories of mental imagery and thought generation that propose involuntary thought intrusion as both an everyday event, and, in extreme cases, a component of mental disorders like PTSD44.Interestingly, it has been recently shown that self-initiated movements can be aborted even after the onset of predictive neural signalsIn summary, we think that the best way to explain our results is not in terms of unconscious decision processes (as it has been advanced previously in the literature), but rather by a process in which a decision (which could be conscious) is informed by weak sensory representations.45. Our results expand that finding by showing that the vividness of future visual thoughts is predicted by information stored in the primary visual cortex.Our current study can be seen as the first to capture the possible origins and contents of involuntary thoughts and how they progress into or bias subsequent voluntary imagery. This is compatible with the finding that the most prominent differences between low and high vividness trials are seen for the pre-imagery period in visual areas, especially the primary visual cortex, which can be interpreted as when one of the patterns is more strongly represented it will induce a more vivid subsequent volitional mental image. This is in line with reports showing that imagery vividness depends on the relative overlap of the patterns of activation elicited by visual perception and imageryIt is up to future research to reveal whether representations biasing subsequent voluntary imagery are genuinely non-conscious or not. This will not only shed light on age-old questions of volition, but also provide a clear mechanism for pathological intrusive thoughts common across multiple mental disorders.https://www.nhmrc.gov.au/guidelines-publications/e72). All participants gave informed consent to participate in the experiment. For the fMRI experiment, we tested 14 participants . We selected the sample size based on both estimations of effect sizes and the number of participants used in previous studies employing decoding to track brain signals predictive of subsequent decisions9. Previous works tested from 8 to 14 participants, we thus used the participant’s number upper bound in order to maximize the reliability of the results. We performed power analyses to corroborate that this number of participants was adequate to achieve a power of at least 0.8. Based on effect size estimations using G*Power 346. Soon at al. study on the pre volitional determinants of decision making9 tested 14 participants achieving a power of 0.812 in the time resolved decoding analysis while Bannert and Bartels study on perception-imagery cross-decoding generalization tested 830. Post hoc effect size analysis revealed that they would have needed to test 12 participants to achieve a power of 0.8. For the behavioral free decision and cued imagery priming task, we invited all the previous 14 participants to be part in this psychophysics experiment. Only 8 participants , were able to come back to complete this new experiment.Experimental procedures were approved by the University of New South Wales Human Research Ethics Committee (HREC#: HC12030). All methods in this study were performed in accordance with the guidelines and regulations from the Australian National Statement on Ethical Conduct in Human Research , which were previously familiar to the participants through prior training sessions. We asked the participants to refrain from following preconceived decision schemes. In the scanner, participants were provided with two dual-button boxes, one held in each hand. Each trial started with a prompt reading: “take your time to choose – press right button” for 2 seconds Fig. . After t17, we developed a novel independent psychophysics experiment to test its reliability. We objectively measured imagery strength as a function of time for a subset of the participants from the fMRI experiment. Importantly, the results of this experiment revealed that the reported onsets of decisions are indeed reliable relative to the temporal resolution of the fMRI , plus 48 catch trials evenly divided among time points.We employed two conditions: free decision (freely chosen imagined stimulus and imagery onset) and cued , see Fig. ons Fig. . We reasons Fig. . Then, eons Fig. . For theRaw priming values were calculated as the number of congruent dominant gratings in binocular rivalry  divided by the total number of trials excluding mixed dominance binocular , for each time point and condition independently. Raw vividness values were calculated as the average per time point and condition excluding mixed perception trials. Priming and vividness were normalized as z-score within participants and across time-points and conditions to account for baseline differences across participants, but otherwise conserving relative differences amongst conditions and time-points. Rivalry dominance self-report reliability was verified with fake rivalry catch trials, where gratings were physically fused and equally dominant, which were reported as mixed above chance level . Priming and vividness z-scores were subjected to a one-way ANOVA to detect main the effects of conditions. We also performed post-hoc two-sample t-tests to verify that priming and vividness scores differed significantly between time points , who had extensive experience as subjects in psychophysics experiments. We further sought to test if these results would generalize to completely inexperienced participants who did not participate in the fMRI experiment (N = 10). We did not, however, find a significant increase of priming or vividness as a function of time as for results on Fig. Scans were performed at the Neuroscience Research Australia (NeuRA) facility, Sydney, Australia, in a Philips 3T Achieva TX MRI scanner using a 32-channel head coil. Structural images were acquired using turbo field echo (TFE) sequence consisting in 256 T1-weighted sagittal slices covering the whole brain . Functional T2*-weighted images were acquired using echo planar imaging (EPI) sequence, with 31 slices .We presented counter-phase flickering gratings at 4.167 Hz . They were presented at their respective predefined colors and orientations . The gratings were convolved with a Gaussian-like 2D kernel to obtain smooth-edged circular gratings. Gratings were presented inside a rectangle . To ensure deployment of attention to the stimulus during the mapping, participants performed a detection task: pressing a button upon seeing a gray dot anywhere on the wedges.To functionally determine the boundaries of visual areas from V1 to V4 independently for each participant, we used the phase-encoding method53 for MATLAB  using in-house scripts. Participants’ heads were restrained using foam pads and adhesive tape. Each session followed the same structure: first the structural scanning followed by the retinotopic mapping. Then the perception task was alternated with the imagery task until completing 3 runs of the perception task. Then the imagery task was repeated until completing 7 or 8 (depending on the participant) runs in total. Pauses were assigned in between the runs. The 4 first volumes of each functional runs were discarded to account for the equilibrium magnetization time and each functional run started with 10 seconds of fixation.We performed the 3 experiments in a single scanning session lasting about 1.5 h. Stimuli were delivered using an 18” MRI-compatible LCD screen  located at the end of the bore. All stimuli were delivered and responses gathered employing the Psychtoolbox 355. We manually delineated boundaries between retinotopic areas on the flattened surface around the occipital pole by identifying voxels showing phase reversals in the polar angle map, representing the horizontal and vertical visual meridians. In all participants, we clearly defined five distinct visual areas: V1, V2, V3d, V3v and V4; throughout this paper, we merge V3d and V3v and label them as V3. All four retinotopic labels were then defined as the intersection with the perceptual blocks  thus restricting the ROI to the foveal representation of each visual area.Functional MRI retinotopic mapping data were analyzed using the Fast-Fourier Transform (FFT) in MATLAB. The FFT was applied voxel-wise across time points. The complex output of the FFT contained both the amplitude and phase information of sinusoidal components of the BOLD signal. Phase information at the frequency of stimulation (0.033 Hz) was then extracted, using its amplitude as threshold (≥2 SNR) and overlaid them on each participant’s cortical surface reconstruction obtained using Freesurfer9. We employed a 14th order FIR basis function encompassing 28 seconds from −13 to +13 seconds from the imagery onset, thus obtaining 14 bins representing each TR. For the perception condition, we employed a 1st order FIR basis function from the onset of each perceptual block to its end (15 seconds). We also employed 1st order FIR basis functions for the sanity check imagery decoding . We realigned functional images to the first functional volume and high-pass filtered (128 seconds) to remove low-frequency drifts in the signal, with no additional spatial smoothing. To estimate the hemodynamic response function (HRF), we generated regressors for each grating  for each run and experiment (perception and imagery) independently. We used finite-impulse response (FIR) as the basis function. This basis function makes no assumptions about the shape of the HRF which is important for the analysis of the free decision imagery dataits end 1 seconds.56. Using a leave-one-run out cross-validation scheme, we trained a L2-norm regularized linear supporting vector machine  on beta values using all but one run and then tested on the remaining one. No additional scaling  was performed on the data as beta values represent a scaled version of the data relative to the run mean. Training and testing was repeated until all runs were used as test and then averaged the results across validations . We performed leave-one-run out cross validation for every temporal bin independently.We used a well-established decoding approach to extract information related to each grating contained in the pattern of activation across voxels of a given participant  using the decoding toolbox (TDT)We also employed cross-classification to generalize information between the perception and the imagery tasks in the “perception-imagery generalization”.st order FIR filter, yielding regressors for red and green perceptual gratings, as explained in the previous section. Imagery trials were pre-processed exactly as in the imagery decoding, yielding time-resolved (2 s) or block (10 s) regressors (see previous section for details). Thus, classifiers trained on the perceptual runs  were tested on the imagery data . Accuracy was calculated as in the imagery decoding , except for that the training-testing procedure was performed only once , since it is not necessary to use cross-validation in such cross-classification schemes as the training and testing data are different and independent (as opposed to the imagery decoding condition where a fraction of the data was used for training and another for testing).For the perception-imagery cross-classification, we trained on the ensemble of the perception runs and tested on the ensemble of the imagery runs. In each perception run, green and red gratings were shown pseudorandomly in 6 blocks of 15 s each. Perceptual blocks (15 s) were convolved with a 157. We then performed a one-tail one-sample t-test against 50% (chance level) across participants for every voxel. We corrected for multiple comparisons using cluster-extent based thresholding employing Gaussian Random Field theory59, as implemented in FSL60. We used a primary threshold of p < 0.001 at the voxel level, as recommended in previous studies61, and a cluster level threshold of p < 0.05 in every time point volume independently. Importantly, these thresholds have been shown to be valid within the nominal false positive ratios62.We employed 2 different decoding approaches: searchlight and region-of-interest (ROI). We used a spherical searchlight of 3 voxels of radius and obtained volumes in which a value of decoding accuracy was assigned to each voxel. We normalized the decoding accuracy volumes into the MNI space and applied a spatial smoothing of 8 mm FWHM, which has been found to be optimal in order to account for anatomical idiosyncrasies across participantsROI decoding was used to test information content in visual areas specifically. We defined the boundaries of visual areas from V1 to V4 which volumes were used as ROI. Note that because visual ROI were defined on the cortical surface , only gray-matter containing voxels were considered, as opposed to the searchlight approach which also considers non-gray matter containing voxels, potentially explaining differences on sensitivity between these approaches.We tested if there was a difference in the average BOLD response between stimuli . We did not find any significant differences  in the average BOLD response Fig. , thus ru63. Previous reports have highlighted the possibility of obtaining skewed decoding distributions, which would invalidate the use of standard parametric statistical tests29. We thus randomly shuffled the labels  among trials and within blocks  for each participant and condition  to generate empirical data under the null hypothesis. After reshuffling the labels, we generated regressors for each stimulus and performed decoding following the same procedure described in the previous paragraph. We repeated this procedure 1000 times and obtained the empirical distribution under the null hypothesis. At each iteration, the second level analysis (across participants) consisted of averaging the results across participants , from which we obtained confidence intervals for each decoding time point and area  under the null hypothesis. To do this, we employed the data from the null distribution obtained with the permutation test . Fig. et al.19). To do this, we shifted the labels by one trial (N-1). Briefly, the rationale behind this control is the following: if there was spill over from the previous trial, this analysis should show higher decoding accuracy in the pre-imagery period as effects from the previous trial would spillover over the next trial . All the decoding details were otherwise identical to what is described in the section “Multi-voxel pattern analysis (MVPA)” except for that the first trial of each run was not considered as there was no N-1 trial in that case. Analogously, for the perception-imagery generalization, training was performed on perception data and tested on imagery trials labeled as N-1.We conducted a control analysis to directly test whether the searchlight results could be explained by any spill over from the previous trial, as performed in a previous study (Soon Supplementary Figures and Tables


Specifically, a behaviour that reduces the fitness of the actor by c and increases the fitness of the recipient by b will be favoured by natural selection when sb > c. We suggest that the coefficient of shared reproductive interest may provide a valuable tool for understanding not only the evolution of human kinship but also cooperation and conflict across the natural world more generally.Cooperation among kin is common across the natural world and can be explained in terms of inclusive fitness theory, which holds that individuals can derive indirect fitness benefits from aiding genetically related individuals. However, human kinship includes not only genetic kin but also kin by marriage: our affines (in-laws) and spouses. Can cooperation between these genetically unrelated kin be reconciled with inclusive fitness theory? Here, we argue that although affinal kin and spouses do not necessarily share genetic ancestry, they may have shared genetic interests in future reproduction and, as such, can derive indirect fitness benefits though cooperating. We use standard inclusive fitness theory to derive a coefficient of shared reproductive interest ( This leads to the prediction that organisms will benefit from recognizing and preferentially cooperating with kin [Hamilton's rule provides a framework for understanding the evolution of altruism among genetically related individuals –3. It stwith kin ,3. In huHowever, human kinship comprises not only genetic kin but also kin through marriage—our affines (in-laws) and spouses. Although the importance of cooperation among affinal kin has frequently been noted by anthropologists –6 cooperr = 0.25. The altruist therefore has a genetic interest in her brother's wife's reproduction. Here, we propose a coefficient that captures the shared reproductive interest between individuals.The central logic of inclusive fitness theory is that when an altruist's genetic kin reproduce, they propagate genes that are identical by descent to those carried by the altruist ,10. Howe2.s). This coefficient measures the genetic interest an altruist has in the future offspring of another individual, expressed relative to its genetic interest in its own future offspring. A derivation of s, starting from Hamilton's rule [In order to measure the fitness benefits that individuals derive from social interactions with kin of all kinds , we propose a coefficient of ‘shared reproductive interest’  and rC is the relatedness of the actor to the actor's mate. Likewise, the relatedness of the actor to the recipient's offspring is given by the average of the relatedness of the actor to the recipient and the relatedness of the actor to the recipient's mate, with whom those offspring will be produced. This yieldsrB is the relatedness of the actor to the recipient and rD is the relatedness of the actor to the recipient's mate. The measures of genetic relatedness (r) that constitute rB′ and rA′ can be defined using either pedigree estimates or genetic markers. Both the ‘actor's mate’ and the ‘recipient's mate’ may refer to a specific individual, or alternatively to an appropriately weighted set of all possible mating partners in cases where there is uncertainty as to this individual's identity . Given the above, the condition for the act of altruism to be favoured iss is the actor's inclusive fitness valuation of the recipient's offspring expressed relative to that of the actor's own offspring and is defined as conditional upon an act of altruism taking place. While r is a measure of genetic equivalence, s is a measure of reproductive equivalence.Let a focal individual A (the actor) interact with a social partner B (the recipient) such that the number of offspring the actor successfully rears to adulthood is reduced by s, consider the relative inclusive fitness interest that women have in their brothers' wives. Although s can incorporate both paternity uncertainty and inbreeding , in this example we assume a non-inbred population characterized by monogamous mating. In such a setting, even though a woman  is genetically unrelated to her brother's wife , the former will nevertheless be related to the latter's offspring by r = 0.25 (i.e. B's offspring will be A's nieces and nephews). As such, the reproduction of individual B is half as effective at propagating A's genes as is A's own reproduction. Accordingly, sAB = 0.5 (a). It is worth noting that the shared reproductive interest (s) between two individuals is not necessarily symmetrical. For example, while A is genetically related to the offspring of her brother's wife, the reverse is not true—A's brother's wife will be genetically unrelated to the offspring of A .To illustrate the application of the coefficient of shared reproductive interest AB = 0.5 a. It is r = 0.5, her reproductive interest in her mother depends upon who her mother reproduces with. In a strictly monogamously mating population, A's mother will mate with A's father, producing full siblings that are as closely related to A as her own offspring. In this case, the shared interest of A in her mother will be s = 1 (b). In a non-monogamous population in which A's mother mates with an individual genetically unrelated to A, the resulting offspring will be A's half-siblings (r = 0.25) and A will be s = 0.5 to her mother (c). Typical r and s values for some standard classes of kin are provided in Next, consider A's relatedness to her mother. While A's genetic relatedness to her mother is be s = 1 b. In a nr mother c. Typica3.The coefficient of shared reproductive interest defined here provides a framework for estimating the fitness benefits that individuals can derive from social interactions with spouses and affinal kin (in-laws) as well as genetic kin. Although we refer to in-laws, a human-specific term, our analysis can be applied to all notions of extended kin through mating. We argue that shared reproductive interest represents a concept that not only is theoretically consistent with inclusive fitness theory and its subsequent derivations and expansions ,13 but aUnlike genetic relatedness, shared reproductive interest is not usually symmetrical. For example, while a mother has an interest in the reproduction of her son's wife, the reverse is not true, an asymmetry that has been advanced for the evolution of the menopause . Similar, we might also add ‘or two daughters-in-law or eight cousin's spouses’.The idea that kinship can explain and predict instances of altruistic behaviour is one of the most important insights in evolutionary theory and can be traced back to Darwin himself . Althoug


Ne) estimates are useful for determining the conservation status of species, yet accurate estimates of current Ne remain difficult to obtain. The effective population size can contribute to setting federal delisting criteria, as was done for the southern sea otter (Enhydra lutris nereis). After being hunted to near extinction during the North Pacific fur trade, the southern sea otter has recovered over part of its former range, but remains at relatively low numbers, making it desirable to obtain accurate and consistent estimates of Ne. Although theoretical papers have compared the validity of several methods, comparisons of estimators using empirical data in applied conservation settings are limited. We combined thirteen years of demographic and genetic data from 1,006 sea otters to assess multiple Ne estimators, as well as temporal trends in genetic diversity and population genetic structure. Genetic diversity was low and did not increase over time. There was no evidence for distinct genetic units, but some evidence for genetic isolation by distance. In particular, estimates of Ne based on demographic data were much larger than genetic estimates when computed for the entire range of the population, but were similar at smaller spatial scales. The discrepancy between estimates at large spatial scales could be driven by cryptic population structure and/or individual differences in reproductive success. We recommend the development of new delisting criteria for the southern sea otter. We advise the use of multiple estimates of Ne for other wide‐ranging species, species with overlapping generations, or with sex‐biased dispersal, as well as the development of improved metrics of genetic assessments of populations.Conservation genetic techniques and considerations of the evolutionary potential of a species are increasingly being applied to species conservation. For example, effective population size ( This population is considered to be a keystone species because of its role in maintaining nearshore marine kelp forests and estuarine sea grasses , a number which was thought to be sufficient to maintain an Ne of 500 even if large losses were to occur from a major oil spill , so that an Ne of 500 corresponds to 1,850 individuals , the US Geological Survey (USGS), the Monterey Bay Aquarium (MBA), and The Marine Mammal Center (TMMC)  and linkage disequilibrium in Rousset, . We perfns Holm, . In addi2.4Structure v2.3.4  throughout the southern sea otter range . In addition, we evaluated geographic genetic variation using the single population spatial autocorrelation implemented with 999 permutations in GenAlEx v6.501  using the linkage disequilibrium information   method on two subsets of otters with known or estimated birth dates between 1995 and 2000, and between 2000 and 2005. In addition, by implementing the LD method on cohorts of otters, we estimated the number of breeders (Nb) across years. We also calculated the estimates of Ne and Nb from demographic life table data using the program AgeNe  were 0.16 across the entire range and 0.011 for the otters in Monterey County. Evaluating a subset of samples from a single year and location revealed no loci that violated Hardy–Weinberg proportions (HWP). However, when analyzing across all samples, ten of the 38 loci violated HWP, and tests for deviations of HWP by cohort found 60 of 887 tests violated HWP  of the southern sea otter, totaling 1,006 individuals, at 38 microsatellite loci, including 819 for which a birthdate could be estimated, 712 individuals where the GPS location of capture/carcass recovery was known, and 176 radio‐tagged animals with observation‐based home range estimates. Table 3.2Structure analyses revealed no significant genetic structure across geographic regions for the entire dataset and when analyzing each sex separately . MSA analysis shows minimal influence of distance on genetic differences except some minimal effects at the largest spatial scales  and the sibship frequency method found an Ne of 485 (95% CI = 424–550). Although Ne was greater in otters born between 2000 and 2004 than for otters born between 1995 and 1999, the confidence intervals overlapped extensively  across the entire population were more than double the genetic estimates ; however, demographic and genetic estimates were consistent for otters in Monterey County , but the range‐wide genetic estimates of Ne were much lower than demographic estimates. Estimates of Ne can vary between computational techniques, by sample size, and with the number of loci used, which makes accurately estimating Ne for wildlife populations difficult  suggests that cryptic structure across the sea otter range may be the primary cause for the discrepancies in methods.Age structuring of populations can bias estimates of Ne within a single system, and those that have found contrasting results to ours. For example, in house sparrows on islands, it was found that genetic estimates of Ne were higher than demographic estimates , with no significant change over the 13‐year study period, and a decrease in genetic diversity when grouping otters by birth year. Although confirmation of consistent genetic diversity over the sampling period is promising, increased diversity would be beneficial to recover what was lost during the bottleneck associated with fur trade hunting , we estimate that the current Ne of the southern sea otter population is between 544 and 1,145. Because Ne is not increasing with the growth of the population, and because we are unable to provide a single precise estimate of the number of otters corresponding to an Ne of 500 as required by the recovery plan, we conclude that the current delisting criterion is not appropriate for southern sea otters. Instead, approaches such as population viability analyses that can incorporate genetic and demographic factors to determine extinction risks could serve to better inform delisting decisions: Such an integrated approach can incorporate the importance of maintaining sufficient genetic variation while encompassing additional factors (Benson et al., Ne itself can be incorporated into recovery plans using it as a risk element as a part of a more comprehensive plan (Allendorf et al., Ne to some extent in nine of eleven recovery plans, for example in setting minimum abundance levels. The plans also include multiple delisting criteria which ensure that the important aspects of Ne are considered but delisting is not based on a specific value of Ne without considering other important factors (C. Busack, NOAA Fisheries, Portland Regional Office, personnel communication; e.g., Hard et al., Our findings highlight fundamental difficulties in defining clear indicators of the genetic status of a population or species (Pierson, Luikart, & Schwartz, Ne can be effectively estimated when the assumptions of the analyses are met. Inconsistencies between the methods across the entire range of the sea otter population, however, revealed the difficulties of accurately evaluating Ne for long‐lived species with large geographic distributions despite no apparent genetic structure. Demographic analyses of Ne may not be possible for some species because acquiring demographic data is expensive, time‐consuming, and requires many years of continued monitoring. In contrast, genetic estimates are effective for small, isolated populations (Wang, Ne but this does not increase precision of estimates (Waples, Larson, & Waples, Ne for wide‐ranging mammal species of conservation concern. For sea otters, as for many threatened populations, multiple independent estimates may be the best approach.We found good agreement between the measures of effective population size within a subset of the range, indicating that ns Wang, , as is tNone Declared.https://doi.org/10.5061/dryad.j992pv8.Microsatellite genotypes have been deposited and made publically available on Dryad Demographic data used in effective population size estimates are included in the supplemental materials and references cited therein. Click here for additional data file.


Signal transducer and activator of transcription 3 (STAT3), a member of the STAT protein family, can be phosphorylated by receptor-associated Janus kinases (JAKs) in response to stimulation by cytokines and growth factors. It forms homo- or heterodimers that can translocate to the cell nucleus where they act as transcription activators. Constitutive activation of STAT3 has been found to be associated with initiation and progression of various cancers. It can exert proliferative as well as anti-apoptotic effects. This review focuses on the role of STAT3 in pathogenesis i.e., proliferation, differentiation, migration, and apoptosis of hematological malignancies viz. leukemia, lymphoma and myeloma, and briefly highlights the potential therapeutic approaches developed against STAT3 activation pathway. Signal Transducers and Activators of Transcription (STATs), were first discovered in 1994 and found to be involved in interferon (IFN)-triggered transcription regulation ,3. To daSTAT3 is an important member of STAT family that regulates gene transcription by relaying signals from activated plasma membrane receptors to the nucleus in response to various stimuli ,14.The N-terminal domain—composed of an oligomerization and a coiled-coil domain.The DNA-binding domain—that can recognize a specific molecular motif in the DNA.A linker domain.The Src homology 2 (SH2) domain—important for the formation of dimers; phospho-tyrosine 705 is important for this dimerization.The C-terminal transactivation domain—This domain differs between the α and β isoforms, with the β form having a unique truncated C-terminal sequence. STAT3 protein also has a Ser 727 phosphorylation site, which though less studied than Tyr 705, is important for regulating STAT3 activation by serine/threonine kinases such as the MAPKs (mitogen-activated protein kinases) .The structure of the STAT3 molecule has several distinct functional domains :The N-teSTAT3, activated by phosphorylation, is a downstream target of several plasma membrane surface receptors that can be activated by a plethora of soluble mediators, including interleukins , other cytokines , and several hormones  ,17. The S727 phosphorylation in STAT3α isoform, necessary for activation, also seems to have an intrinsic regulation mechanism for limiting STAT3 activation through dephosphorylation of Y705 by the nuclear TC45 phosphatase . STAT3β,Cyclin D1, c-Myc), survival , angiogenesis , and metastasis (MMPs), but also inhibit anti-tumor immune responses [STAT3 was first exhibited to play a role in cancer growth by Yu et al. in 1995, whose study suggested that the STAT3 activation can lead to regulation of oncogene expression . Since tesponses . Conversesponses ,36. Collesponses ,31, thusSTAT3 has an important part in promoting leukemogenesis in hematopoietic stem cells. Its overexpression has been seen in malignant hematopoietic stem cells (HSCs) in Acute Myeloid Leukemia (AML) and Myelodysplastic syndrome MDS, thus insinuating that STAT3 plays a crucial role in the development of malignancies . ConstitSTAT3 has been shown to play a critical function in promoting tumor growth, increasing survival of cancerous cells, promoting resistance to chemotherapy, and linked with an increased likelihood of AML relapse in patients ,44. The Lymphoma is defined as the solid tumor of lymphocytes and can be broadly classified into two categories: Hodgkin’s Lymphoma (HL) and Non-Hodgkin’s Lymphomas (NHL) . Gene exBcl-2 and Bcl-xL; that have been implicated in cell survival and decreased susceptibility to apoptosis [Hodgkin’s lymphoma (HL) manifests constitutive activation of the JAK-STAT signaling pathway in the neoplastic cells which, in classical HL, are called Hodgkin’s Reed–Sternberg (HRS) cells ,50. Conspoptosis . Also, spoptosis , inhibitpoptosis , and canpoptosis .NHL make up around 90% of all malignant lymphomas  and are Multiple myeloma (MM) is the second most common hematological malignancy, marked by an accumulation of abnormal clonal plasma cells in the bone marrow . SeveralAs discussed above, most hematological malignancies manifest elevated levels of constitutively activated STAT3 and enhanced downstream transcriptional profiles in accordance with STAT3 regulated genes ,14,71,72Broadly, two strategies can be employed for STAT3: (1) Direct inhibition and (2) Indirect inhibition . VariousPsoralea corylifolia. Besides its estrogen-like activities, it has also demonstrated anti-tumor and anti-bacterial effects [Bavachin is a plant estrogen-like compound purified from plants such as  effects . It has  effects .Butein is a tetrahydroxychalcone derived from plants related to cashews. It has been demonstrated to have a STAT3 inhibitory effect in various cell types including multiple myeloma (MM) cells. Deterioration of both constitutive and inducible STAT3 activation in MM cells by butein is shown to be mediated through the interruption of the upstream kinases c-Src and JAK 1&2 ,88. ButeTripterygium wilfordii, celastrol has been used in traditional Chinese medicine since time immemorial. In the modern context, it has been demonstrated to exert anti-cancer effects in various cancer models such as MM, AML, and hepatocellular carcinoma [Derived from the plant arcinoma ,90,91. Carcinoma . It has 2/M cell cycle arrest. The cells exhibited inhibition of STAT3 phosphorylation in a dose-dependent manner. However, the exact mechanism of STAT3 abrogation in these cell lines remains unclear, although diverse molecules have been found to mediate STAT3 suppressive effects of cucurbitacin B in other solid tumors [Cucurbitacins are an imperative part of herbs used in many traditional Chinese medicines  and haved tumors ,94.The anti-leukemic effects of GS was initially reported by Samudio et al.  when theMagnolia officinalis, is widely acknowledged as an antimicrobial and anti-inflammatory in traditional Chinese medicinal practice [Honokiol (HNK), a biphenolic small molecular weight natural product extracted from the bark and leaves of practice . In multpractice ,100,101.practice . HNK waspractice . Withania somnifera and shown to have antiproliferative properties in several cancer types. It has also been demonstrated to have other medicinal effects such as anti-inflammatory, anti-oxidant, and cardiovascular protection [Withaferin A (WFA) is isolated from the plant otection . In the otection . The finNatural compounds have demonstrated promising effects in laboratory settings; however, it would take considerable time for them to reach clinics for widespread patient use. Although these compounds have promising low toxicity profiles, they face challenges such as specificity of targets, potency and efficacy, and their mechanisms of action being undefined or understudied. However, there are available a host of chemically synthesized molecules that exhibit promising STAT3 inhibiting activity and, in many cases, can abrogate tumor growth. Here, we describe some of these synthetic molecules with relevance to their use in hematological malignancies and their ability to act via direct or indirect STAT3 inhibition.Bcl-xL and cyclin D1 [Direct inhibitors, as the name suggests, interact directly with the STAT3 domains to antagonize STAT3 activation. These small molecules mainly interact with either the amino-terminal domain, SH2 domain, or DNA-binding carboxy terminal domain of STAT3 molecules. The compounds showing promising activity in targeting STAT3 in hematological malignancies include PY*LKTK, PY*L, AY*L , and ISSyclin D1 . More diyclin D1 .STAT3 is a multistep signaling cascade involving a multitude of components. This provides an opportunity for the development of compounds that can interact with other constituents of the pathway and thus abrogate STAT3 activity in a defined manner. One of the foremost approaches to indirect STAT3 inhibition is receptor antagonism. As STATs are downstream to several cytokine and growth receptors, especially in MM and leukemias, monoclonal antibodies blocking these receptors represent a promising choice. As a proof of concept, the chimeric antibody rituximab has shown inhibition of constitutive STAT3 activity by blocking the CD-20 receptor in Non-Hodgkin’s Lymphoma. The blockage was demonstrated to downregulate IL-10, leading to STAT3 inhibition .617F JAK2 mutation, as revealed in a phase 1–2 clinical trial of myelofibrosis patients. Another synthetic compound INCB20 potently disrupts the activation of all members of the JAK family, and thus blocks the IL-6 mediated progression of MM. It also blocks SH-2 phosphorylation, thus abrogating cytokine mediated dexamethasone resistance [In MM, JAKs can be activated by IL-6 present in the bone marrow micro-environment. This leads to recruitment of two gp130 signal–transducing subunits to the receptor complex; consequently, gp130-associated JAKs  become activated to provide docking sites for STAT3 . Therefosistance .Other than JAK activation, elevated levels and/or kinase activity of Src and other growth factor receptors have been indicated in several cancers, causing activation of STAT3. These also make important potential targets to check STAT3 activity. One such molecule is Dasatinib, which can inhibit SFK and BCR/ABL activation and has been approved for use as second line treatment in patients with chronic myelogenous leukemia and also for Philadelphia chromosome–positive ALL . AlthougTargeting STAT nuclear translocation is yet another potential approach to develop efficacious anti-cancer drugs. The activity of phosphorylated STAT3 as a DNA-binding transcription factor depends upon the trafficking of homodimers from cytosol and into the nucleus . One sucSTAT3 proteins exhibit negative regulation by 3 major protein families: (1) Phosphotyrosine phosphatase (PTP) which regulates its activity by dephosphorylating upstream kinases ; (2) PIASeveral hallmarks of cancer, such as uncontrolled cellular proliferation, invasion/metastasis, and resistance to apoptosis, are associated with dysregulated STAT signaling. In the context of hematological malignancies, aberrant STAT3 activation becomes an even more important factor in tumor pathogenesis due to the constant presence of cytokines and growth factors in the bone marrow microenvironment. Although not the only transcription factor involved in tumorigenesis, its inhibition has been shown to prevent malignant transformation in leukemias and lymphomas. Elucidation of multifaceted STAT3 signaling cascade using multi-omics approaches can lead to deeper understanding of its pathological role in the development of malignancies and their progression.In conclusion, it can be reconciled that STAT3 has been validated as a druggable target and important pathway in cancer therapeutics. Our lab and other pharma-oncology groups are working with various classes of pharmacological blockers of STAT3 signaling, and important advancements have been made in recent years to develop clinically relevant drug candidates for STAT3 inhibition. Although it remains a challenge to develop a truly potent and specific STAT3 inhibitor, the current compounds can serve as great leads to develop better and efficacious anticancer therapies.


Marmota marmota), a large ground-dwelling squirrel exquisitely adapted to the “ice-age” climate of the Pleistocene steppe [Some species responded successfully to prehistoric changes in climate , 2, while steppe , 5. Since steppe , 7. Geno •The Alpine marmot is among the least genomically diverse animal species•Its diversity was lost during consecutive ice-age climate-related events•An extreme lifestyle hampered the subsequent recovery of genetic variation•Alpine marmots show why large populations can coexist with very low genetic variation Despite being highly abundant and well adapted, Gossmann et al. report that the Alpine marmot is among the least genetically diverse animal species. The low diversity is found to be the consequence of consecutive, climate-related events, including long-term extreme niche adaptation, that also greatly retarded the recovery of its genetic diversity. Marmota monax)  analysis)  . The cytWe next studied the genome-level diversity of the Alpine marmot. Unexpectedly, the within-individual diversity was found to be remarkably low, with a heterozygosity of 0.12 per kilobase A. To plas, across the genome, and typical levels of relatedness  within an otherwise diverse population . The latatedness C, runs oatedness , and theatedness . Resultsatedness C and sugS = 0.037% versus πS = 0.033%), and for the mitochondrial genomes, all Gsies and Mauls marmots descend from the most recent common ancestor of the LGS sample  contain a high proportion of close relatives A, but thS sample C. This sS sample C. Taken N/πS: LGS 33.7%; Mauls 37.5%; Gsies 39.0%; combined sample: 34.6%; Nes < 10), where selection might become ineffective, following any further drop in Ne  mammals. Previous work has shown that species-wide diversity across a broad range of animal species is well predicted by their “propagule size,” i.e., the size of the life stage that leaves its parents and disperses . The Alp with πS B. In botffspring D. These While correlations of genetic diversity with life history are well established, it remains unclear exactly why they hold. One possibility is that a species’ life history has a major influence on its response to demographic perturbations, such as major changes in climate . Such evS, we can estimate the genetic diversity of this ancestral marmot population .By combining the population size estimates F, and ouMarmota .Requests for further information should be directed to and will be fulfilled by the Lead Contact, Markus Ralser  each were obtained from three wild Alpine marmot populations in the Central Alps near Mauls , around St Martin, Gsies,  , and in the nature reserve of La Grande Sassière . All animals were from different families. The animals’ sex was confirmed by genome analysis . ItalianMus musculus, To sequence, assemble and annotate a reference genome for the Alpine marmot A includiGenomic DNA was extracted from spleen, liver, bone and hair tissues by the QIAamp DNA Mini-Kit (QIAGEN) according to the manufacturer’s instructions (including proteinase K digest to obtain high molecular weight DNA). To create the Alpine marmot reference genome, we sequenced an animal from the most centrally located population (Mauls I) using Illumina Hiseq 2500 short read and Roche / 454 long read sequencing technologies. We constructed paired end , mate pair (“gelfree” library (MP3000) and 5kbp, 10kbp and 20kbp gel selected fragment size, Nextera Mate Pair Kit) and Roche/454 single read libraries. We produced a high sequencing coverage based on the paired end libraries and supplementary lower coverage using the matepair libraries and the 454 technology  to the Newbler assembly .Ictidomys tridecemlineatus) and the house mouse (Mus musculus) MM10 genomes. We used whole genome alignments which were done using the LAST aligner δaδi analM. vancouverensis and other rodent species. The Alpine marmot data come from individual published sources [To compare the diversity at microsatellite loci of the Alpine marmot to other mammal species, we plotted the number of microsatellite alleles against the expected heterozygosity in a wide range of published datasets C. We sho sources , 84, whi sources .g), litter size, and gestation length (days), and can be considered as a measure of “reproductive output,” in which species vary according to their investment in offspring “quality” versus “quantity.” The other factor includes contributions from interbirth interval, weaning age, and age at sexual maturity , and can be considered as a measure of “reproductive timing,” in which species vary on a “fast-slow” continuum. PanTheria database [To compare the life history of the Alpine marmot to other Eutherian mammals D, we foldatabase , which idatabase .Male rats  and male mice  (Charles River Laboratories) were housed in conventional cages at room temperature with a 12-h light/dark photoperiod. All procedures were carried out in accordance with UK Home Office protocols by a personal license holder.Lipids were extracted from 50mg of Alpine marmot, rat or mouse white adipose tissue as previously described . SamplesStatistical tests were conducted with appropriate packages in R and Python.http://public-genomes-ngs.molgen.mpg.de.The Alpine marmot genome is made available at NCBI  and ENA


Parasite infections can have substantial impacts on population dynamics and are accordingly a key challenge for wild population management. Here we studied genetic mechanisms driving parasite resistance in a large herbivore through a comprehensive approach combining measurements of neutral (16 microsatellites) and adaptive (MHC DRB1 exon 2) genetic diversity and two types of gastrointestinal parasites (nematodes and coccidia).While accounting for other extrinsic and intrinsic predictors known to impact parasite load, we show that both neutral genetic diversity and DRB1 are associated with resistance to gastrointestinal nematodes. Intermediate levels of multi-locus heterozygosity maximized nematodes resistance, suggesting that both in- and outbreeding depression might occur in the population. DRB1 heterozygosity and specific alleles effects were detected, suggesting the occurrence of heterozygote advantage, rare-allele effects and/or fluctuating selection. On the contrary, no association was detected between genetic diversity and resistance to coccidia, indicating that different parasite classes are impacted by different genetic drivers.This study provides important insights for large herbivores and wild sheep pathogen management, and in particular suggests that factors likely to impact genetic diversity and allelic frequencies, including global changes, are also expected to impact parasite resistance.The online version of this article (10.1186/s12898-019-0228-x) contains supplementary material, which is available to authorized users. Parasites are an important component of ecosystems and can have substantial impacts on host fitness and population dynamics. Parasites can affect body condition e.g. –3), repr, repr3])host’s ability to interact with and control the lifecycle of the parasite” 95%).The prevalence of coccidia was 100% with FOC ranging from 25 to 11,300 OPG (median FOC = 925). GINs were present in 76 out of 77 individuals with FEC ranging from 0 to 5100 EPG (median FEC = 350). Repeated measurements were available for 29 individuals (70 observations) and mean repeatability for FOC was 0.08  and included age, body condition, time lapse between sampling and coproscopy, and Julian date .Almost all GINs models including genetic predictors (16 out of 19) had a lower AICc than the non-genetic model, highlighting the strong relationship between GINs resistance and genetics. In particular, the model including DRB1 heterozygosity (model set (i)) was the best model (lowest AICc), indicating that among the three DRB1 characteristics evaluated , heterozygosity was the best descriptor of parasite resistance for GINs. The model including both sMLH/sMLHle Table  and its g2 and the “global/local” test did not lead to same conclusions, we were not able to distinguish between local and global effects of neutral genetic variation. It seemed that DRB1 candidate locus conferred a heterozygote advantage and that rare alleles and/or fluctuating selection might also occur in the study population [As illustrated here, parasite resistance in the female Mediterranean mouflon is a complex trait controlled by several non-genetic and genetic predictors. For both parasite classes, individuals in better condition were less parasitized. Multi-locus heterozygosity was linked to GINs resistance through a U-shaped relationship suggesting the presence of both in- and outbreeding depression in our population. However, since pulation . These rpulation . In contpulation , 86), emNone of the genetic predictors studied were linked with coccidia resistance. The absence of correlation between genetic diversity and parasite resistance was also observed in other host-parasite systems e.g., , 92, 93), 9392, 9Differences between results for coccidia and GINs may be due to the fact that coccidia are intracellular protozoa, while GINs are macro-parasitic nematodes. Micro- and macro-parasites are thought to be controlled by different immune responses  thaFalco naumanni [Leuciscus leuciscus [Cyanistes caeruleus [We observed a U-shaped relationship between sMLH and GINs burden with a maximal parasite resistance obtained for individuals with intermediate heterozygosity levels. Parasite burden decreased with increasing heterozygosity until a threshold (~ 1), after which highly heterozygous individuals were parasitized as much as highly homozygous individuals, suggesting the presence of both positive and negative HFCs. While a positive relationship between parasite resistance and genetic diversity is the rule e.g., , 79, 96), 9679, 9naumanni ; rostrumeuciscus ; raccooneuciscus ; blue tiaeruleus ) but mosaeruleus , 97, 98)aeruleus , 99. Indaeruleus . AccordiA positive relationship between genetic diversity and fitness-related traits such as parasite resistance can be explained by inbreeding depression with more inbred individuals exhibiting lower levels of heterozygosity and fitness . On the g2 was not significantly different from zero, preventing us from coming to a conclusion about global or local effect of multi-locus heterozygosity. Detection of significant identity disequilibrium using g2 is only rarely achieved  and numved . Hal tests  but see al tests ).Links between MHC heterozygosity and fitness were evidenced across a wide range of taxa . However, models containing alleles were among the best models, and specific allele effects might more likely be due to the immunological properties of their products (i.e. peptide binding sites in our case). Specific MHC and DRB1 allele effects on fitness and parasite resistance were observed elsewhere . Ss sierra . Similars sierra –134. Fins sierra  posits ts sierra  but see s sierra ). Since s sierra , 138–140The Mediterranean mouflon study population originates from the release of 19 individuals between 1956 and 1960  in a NatNf, Cf and Sf, see [The population has been monitored each year since 1974, mainly during spring and early summer (April–July), by capture-mark-recapture. Animals were baited with salt and captured using individual or collective traps and dropping nets. When captured, animals were marked with a numbered/colored collar; biometric measurements were made and hairs and faeces were sampled for genetic and coproscopic analyses. Genetic analyses revealed that gene flow is mostly insured by male reproductive dispersal , while  Sf, see ) and gen Sf, see .www.antagene.com) following the procedure presented in Portanier et al. [inbreedR package for R software [g2, a measure of the covariance in heterozygosity using Robust Multi-locus Estimates of Selfing software  using tsoftware . To detere (RMES ) with 10The second exon of the MHC-DRB class II gene encoding the ligand-binding domain of the protein was amplified and sequenced for all individuals. Each sample was analyzed twice by at least two independent technical replicates. Briefly, we performed the two-step PCR strategy combined with the dual-index paired-end sequencing approach described in Galan et al. . During In the candidate gene approach, we also genotyped a microsatellite located in the gamma interferon gene -γ) known to be linked with parasite resistance in wild sheep . HoweveTrichuris spp., Moniezia spp. or Dicrocoelium spp. but the most prevalent are strongylid nematodes and coccidia . Wia spp., ). FEC ania spp., ). After ia spp., ).Cf, Nf and Sf socio-spatial units, respectively) since spatial structure of the population, when overlooked, can lead to spurious HFCs [Prior to testing for genetic effects on FEC and FOC we first identified (and accounted for) other intrinsic and extrinsic variables known to impact parasitism , 156–158ous HFCs .We applied a two-stage procedure in a linear mixed model selection framework, first identifying for each response variable the best non-genetic model  to which genetic predictors  were then added. The predictors included in non-genetic models can also have a genetic basis  but arevif.mer function [2c) and marginal (R2m) R2, representing the variance explained by the fixed and random effects and by the fixed effects alone, respectively.All continuous variables  were centered and scaled  before analyses and individual identity and year of sampling were included as random effects to account for repeated measurements and measurements made in different years, respectively. We also tested for possible non-linear relationships between FEC and FOC and continuous variables by adding their quadratic terms in models. If the addition of the quadratic term did not improve the model by more than two AICc units ΔAICc > 2), only the linear term was retained to perform model selection. Multi-collinearity of predictors was checked using variance inflation factors . Followfunction , if a pr, only thF-ratio test. If the “local” model explains more variance than the “global” model, the local effect hypothesis will receive more support than the global one. Since there are relatively large differences in loci heterozygosity levels , we alsels (see , in whicee [lme4  and MuMIpackages  of R 3.3packages . Signifi package  and mode package  of R 3.3 package . The codAdditional file 1. Results of non-genetic model selection.Additional file 2. Normality tests of non-genetic and genetic models.Additional file 3. Variance Inflation Factors values for genetic models and tests of the presence of sMLH quadratic effects on FOC and FEC.Additional file 4. R code used for statistical analyses.


Domesticated crops show a reduced level of diversity that is commonly attributed to the “domestication bottleneck”; a drastic reduction in the population size associated with subsampling the wild progenitor species and the imposition of selection pressures associated with the domestication syndrome. A prediction of the domestication bottleneck is a sharp decline in genetic diversity early in the domestication process. Surprisingly, archaeological genomes of three major annual crops do not indicate that such a drop in diversity occurred early in the domestication process. In light of this observation, we revisit the general assumption of the domestication bottleneck concept in our current understanding of the evolutionary process of domestication. In plants, domestication results from the selection of a group of traits collectively termed “domestication syndrome” that make them better suited to the human environment  is about 63.3 when drift and selection are equable. Therefore, for a selection coefficient (s) of 0.015, such has been found for maize  would need to be considerably larger than 4,220 individuals to counter the effects of drift. The equivalent Nes value for inbreeders is 3.5. Consequently, at these population sizes purifying selection begins to fail and deleterious mutations are expected to become incorporated into the population at a drift‐determined rate. Therefore, the domestication bottleneck is expected to lead to an increase in the incorporation of deleterious mutations, or the “mutation load” ; then, both He and π estimates should reduce proportionately. We observed that a linear relationship holds between π and He up to a threshold of 30% heterozygous sites tolerated, above which He is disproportionately inflated relative to π, suggesting our 25% heterozygous cutoff is reasonable for this data set.SAMtools  and individual heterozygosity (He)  data set of Swarts et al.  to calcuF. We determined the expected levels of heterozygosity associated with nucleotide diversity for given levels of inbreeding (see Plant accessions maintained in germplasm banks may over time suffer a loss of genomic diversity and become inbred even though the population as a whole maintains the overall nucleotide diversity. This is particularly a concern for inbreeding species such as barley. Therefore, we first assessed the use of heterozygosity as a measure of diversity by comparing the nucleotide diversity of populations with the average genomic heterozygosity of members of the same populations Figure . Under iding see  to gaugeding see , Figure ding see , maize pding see . Previouding see , and eviding see .For barley, we constructed pseudopopulations by clustering barley accessions on the basis of genomewide similarity see . In all,We then compared levels of heterozygosity in sorghum, maize, and barley across time Figure . Maize aBarley shows little change in heterozygosity over time with an increase in variation in heterozygosity apparent in the 6,000‐year‐old genomes of the Yoram Cave barley relative to the wild progenitor Figure d. SimilaIn all three major crops, there is no apparent indication of the dip in genetic diversity at the individual genome level expected from a domestication bottleneck. The discord between nucleotide diversity and heterozygosity in barley and maize illustrates a requirement to rethink how genetic diversity evidence is interpreted in terms of domesticate origins. The heterozygosity evidence suggests some of the subdivided wild populations gave rise to domesticates without meaningful loss of genetic diversity. This is not a bottleneck scenario, and moreover, genetic diversity in wild populations isolated from the progenitor populations of domesticated crops should not contribute to interpretations of lost diversity during domestication.3.1The lack of a dip in genetic diversity that could be associated with a distinct bottleneck episode suggests a disconnect between an intensification of selection, such as from sickle technologies (Allaby et al., A corollary of this scenario regards the mutation load, which hitherto has been regarded as a “cost of domestication.” Under a continuous erosion of genetic diversity through repeated bottlenecks, we should expect a pattern in which mutation load increases over time. This notion is supported by recent findings in which the mutation load in horses was found to increase some time after domestication (Librado et al., The process of domestication cannot be pinned down to a specific point in time as different traits of the domestication syndrome were selected for at different times through changing behaviors (Fuller, Allaby, & Stevens, 3.2It has been observed in recent years that the perennial crops apple and grape do not show evidence of a domestication bottleneck (Gross, Henk, Richards, Fazio, & Volk, None declared. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Age-related macular degeneration (AMD) is the leading cause of blindness in industrialized countries. It is a multifactorial disease of the retina modified by environmental/individual (e.g. smoking) and genetic factors. 34 independent genomic loci are associated with the risk to develop AMD; an interaction between smoking and genetics is currently investigated. It is unclear how the knowledge on the strong genetic component has entered the knowledge base of practicing ophthalmologists, and how they inform and counsel their (AMD) patients about it. In this study, we explore the ophthalmologists’ view on AMD genetics, and their inclination towards communicating genetic risks to patients.We recruited a purposive sample of thirty German ophthalmologists , who took part in a recorded semi-standardized interview. Transcripts were analyzed using content analysis.The majority of office-based ophthalmologists claimed to be unfamiliar with genetics of AMD, in contrast to hospital-affiliated ophthalmologists. Both office and hospital ophthalmologists were convinced that genetics lacks practical relevance in everyday patient care. Many withhold information on heritability or genetic background of AMD from patients and their relatives, for fear of unsettling those individuals. The relevance of the genetic component of AMD or an individuals’ high genetic risk for prevention, e.g. screening or lifestyle modifications in persons with adverse genetic profile, was rated low.Developing genetic educational programs tailored to the routine care of ophthalmologists may be indicated, as well as a better two-way communication between research and practice. Exploring patient views about their expectations to being informed about genetic disease etiology, or about their individual risk, would help inform communication strategies. Age-related macular degeneration (AMD) is the leading cause of blindness in industrialized countries. Its prevalence increases with age; in the population over the age of 65 years, 15–24% are affected by early stages of AMD, according to European population-based studies . The preCFH gene on chromosome 1  seems to run. I’m not aware of the reason for this. I think this is not exactly known. …But to be honest, genetics is certainly an issue that I’m not well informed about.IP 05 o)(what the University delivers to my doorstep” (IP 09 o).Many private practitioners did not actively search for scientific information, but usually rely on being informed automatically in case of significant developments, using, as one interviewee put it, “If there really is a big breakthrough, then I will get to know it anyway, by a CME course at the University or by a drug rep, because they need to sell this knowledge to the customers.IP07 o) but we also talk to colleagues from the Institute of Human Genetics here on a regular basis, as we work together in that field.IP 22 h) struggle in the hospital, there’s much stuff that gets lost, and then you don’t have so much time to trawl all these papers [for genetics].IP 16 h). When you look into PubMed, (…) there are new things coming up every week, and I have a hard time sometimes to judge how relevant a new finding is—is it really something new, or is it just the same that had been published in 2005 and 2006?.IP 26 h)., all ophthalmologists in both samples stressed that genetics did not play a role in the daily routine care of AMD patients. Genetic research and its results were described as ‘As far as genetics is concerned, this is partly in striking contrast to your everyday job—which is very much about mundane stuff. It is about whether the expenses for a walking stick are reimbursed, and not about whether some chromosome is somewhat crooked.IP 03 o)(What is the geneticist doing? What? What? Are they trying a shot in the dark? What do they want? Why are they doing research? Do they have a clear direction? It may well be that this direction is completely contrary to ours.IP 13 o)(rather one sentence only’ (IP 22 h), e.g. just mentioning that the macular degeneration can be hereditary, which is also attributed to time constraints.Some office-based ophthalmologists, and most of the hospital employees, report that they principally educate their AMD patients on the genetic background of their disease. Normally this education is only rather superficial, ‘We don’t say something about special mutations… We say: ‘There may be a genetic component. There are hints that it can run in the family.’ That’s all we say about it.IP 19 h). and being asked about these persons’ individual risk to get the disease. The interviewed ophthalmologists have different strategies to deal with this request: The office-based ophthalmologists mostly screen the patients using fundoscopy, reassure the patients in case of a normal finding, and recommend regular check-ups every couple of years; some hand out Amsler grid cards, a simple device to self-test for distortions in a person’s vision. None of the interviewed ophthalmologists recommend genetic testing or calculating risk scores. Amongst the hospital employees only a few interview partners stated that they would give some further advice to the patients or their relatives in case of questions.The main focus is the patient, but (…) if the children are present, they often ask [about their risk]. Then I willingly tell them (…) that there is an inherent and an age-related component. And then actually I always recommend them to have their eyes examined.IP 23 h); the predictive value was believed to be very low .One office-based ophthalmologist (IP 08 o) was convinced of the reliability of available genetic tests, and supported the use of these tests; all other interview partners were opposed to genetic testing. Among the office-based ophthalmologists, there were many interview partners who considered available genetic tests pre-mature or even dubious (“you can’t change anything about it if someone has the genes” (IP 06 o), to more sophisticated argumentations about preventive measures.Beside this skepticism regarding the technical characteristics of genetic tests, the majority of interview partners—both office-based and hospital-affiliated—expressed the view that predicting the AMD risk genetically would not have any helpful preventive  consequences. The arguments for this view ranged from simple statements along the lines of “If somebody has a completely normal vision, what’s in it for them if they have their genes checked? …with AMD, what are the consequences for this person, what’s their big advantage? You don’t know at all how the [trait] expression will be, and then an additional mental problem will be generated.IP 07 o). When you test a 20-year-old, and tell him or her: ‘Well, now we wait till you’re 60, and then we will start with the AMD prophylaxis’, then there is no need to test them with 20 in the first place.IP 25 h) first hints that patients with certain gene variants obviously react better to a medication, for example Lampalizumab, when treated for dry AMD, and possibly some sort personalized therapy will exist in the future. But for the time being, this is still a long way off.IP 20 h). The doctors would even be reserved when directly asked by relatives about their risks. None of the interviewees has ever discussed (results of) genetic testing with their patients yet, the majority  would advise against it if directly consulted on this.The number of 30 interview partners is small, so it cannot be assumed that the findings presented here are representative of the views of all ophthalmologists in Germany. However, the aim of qualitative studies is not to receive representative data, but to gain a deeper understanding of social and psychological processes and to capture the subjective views and experiences of the persons interviewed. Using a qualitative study design allowed us to tap personal attitudes and professional experiences of doctors that are not readily expressed in response to survey questions , and thaThe bulk of literature on medical doctors’ knowledge and training needs on genetics is focused on hereditary cancer, mostly breast cancer and colorectal cancer. Surveys among specialists in different countries revealed a lack of (perceived) knowledge and an ambivalent attitude towards genetic testing in cancer , 37, eveDoctors have been envisaged to be key players in properly incorporating progress in genetics and DNA technologies in the health care system. This has been emphasized mainly with a view to hereditary cancer, where doctors are expected to help implement needs-based genetic testing and personalized therapy . In termThe overall attitude of the interviewees towards genetics of AMD was so skeptical that even better strategies to distribute and communicate genetics information may be futile, as ophthalmologists may not be willing to invest time in acquiring knowledge and attending educational sessions at all. Knowing about heritability or genetic background of AMD does, for the time being, not influence the treatment of manifest patients, thus the ophthalmologists rated the clinical utility of genetics low. Informing AMD patients that their offspring may carry a certain disease risk was rejected by the majority of interviewees, as was recommending a genetic AMD test to patients with other eye conditions who have relatives suffering from AMD. The main reason was that preventive measures were seen as ineffective, or that the genetic information was considered psychologically unsettling. We found that the focus of ophthalmologists is clearly the management of a manifest disease, and the concept of prevention is not yet well integrated into the routine patient care of the interviewed ophthalmologists. This can also be put down to contradictory or unsatisfying evidence on the effectiveness of different preventive measures (e.g. nutrition), and the unspecific character of preventive lifestyles in question .It has to be discussed whether the ophthalmologic clinic or practice is a suitable place for preventive measures, or whether other channels should be used, e.g. campaigns informing the public about AMD, screening possibilities and risk behaviors. Some doctors also raised the point that it is difficult for them to address accompanying relatives of AMD patients, as those are, strictly speaking, not their patients, and the doctors may even be suspected to just recruit new patients for their practice. This highlights a special need for care concepts for diseases with clear genetic background, as the genetic information has consequences not only for the patient, but also for his or her relative. Practitioners may benefit from guidelines of how to act (or react) without needing to fear that they intrude upon their patient’s and relatives’ privacy or unnecessarily worry them.On the whole, ophthalmologists may underestimate patients’ interest in prevention and genetics. Studies show that patients would welcome their doctors  to discuss genetic aspects of their disease with them . SimilarMany authors have criticized that genomic research discoveries are not translated to be applicable in clinical practice and to population health benefits . In AMD Some authors also point out that translational research and knowledge transfer needs to involve clinicians, proposing that the models conceiving translation as a ‘pipeline’ or a unidirectional pathway (moving from the laboratory to the clinic) need to be overcome in favor of an ‘interlocking loop’ model  or a ‘twundetected genetic risk can have serious consequences for the entire family, for example through preventing access to screening or preventive drugs…resulting in increased morbidity…., family burden and healthcare costs’ [Genetic research on AMD has made enormous progress over the last decade, showing that several genetic susceptibility factors strongly impact AMD risk. With current evidence of some lifestyle factors modulating epigenetic marks, some of the genetic risk might be modifiable by life style. Our study indicates that this knowledge has not had any impact on clinical ophthalmologic practice yet, neither by private practitioners, nor by ophthalmologists employed by hospitals. Even among those doctors who are aware of the genetic aspects of AMD, many withhold this information from patients and their relatives, because of the uncertainty of predicting AMD and for fear of unsettling those individuals. Preventive efforts for late AMD based on genetic information are seen as irrelevant. These findings highlight a need for genetic educational programs tailored to the concerns and routine care situations of ophthalmologists. With the existing evidence that genetic factors convey a substantial AMD risk, it becomes important to perform studies that involve the relatives of AMD patients and explore their views on information, genetic testing and/or clinical screening. These investigations are fundamental to guide future strategies of ophthalmologists  to address patients whose parents suffer from AMD. In addition, long-term clinical studies need to be initiated to assess the benefit of preventive measures in those individuals that were tested to have an elevated or high genetic risk score for AMD. It is honorable that ophthalmologists intend to act responsibly in the favor of their patients by not unsettling them with uncertain predictions of a disease that may lead to blindness; on the other hand, one has to consider that ‘e costs’ .