Miniopterus schreibersii) across Europe. Both markers retrieved general patterns of weak range-wide differentiation, little sex-biased dispersal, and strong isolation by distance that associated with significant genetic structure between the three Mediterranean Peninsulas, which could have acted as glacial refugia. Microsatellites proved uninformative in individual-based analyses, but the resolution offered by genomic SNPs illuminated on regional substructures within several countries, with colonies sharing migrators of distinct ancestry without admixture. This finding is consistent with a marked philopatry and spatial partitioning between mating and rearing grounds in the species, which was suspected from marked-recaptured data. Our study advocates that genomic data are necessary to properly unveil the genetic footprints left by biogeographic processes and social organization in long-distant flyers, which are otherwise rapidly blurred by their high levels of gene flow.Despite their paramount importance in molecular ecology and conservation, genetic diversity and structure remain challenging to quantify with traditional genotyping methods. Next-generation sequencing holds great promises, but this has not been properly tested in highly mobile species. In this article, we compared microsatellite and RAD-sequencing (RAD-seq) analyses to investigate population structure in the declining bent-winged bat ( Patterns of genetic variation, differentiation and admixture inform on the history of populations and thus help understanding the ecological and geographic processes shaping biodiversity in space and time4. Molecular assessments also offer a swift alternative to traditional monitoring techniques , especially when it comes to measuring individual movements, population fragmentation and other key parameters relevant for conservation such as inbreeding and local adaptation7. As such, genetic surveys have become an essential part of the management of threatened species9, by assisting the design of conservation strategies to enhance population connectivity10, restore bottlenecked populations11, and plan translocation/reintroduction efforts in respect to evolutionary units12.A comprehensive picture of the genetic structure of populations is instrumental to any ecological, evolutionary and conservation research14. The issue is also characteristic of genetically impoverished species that experienced range-wide demographic changes, such as refugial bottlenecks and post-glacial expansions, and for which the remaining diversity might be too low to quantify population connectivity4. Moreover, at times in the life cycle, momentary gatherings of individuals from various geographic origins might also blur the appreciations of genetic diversity and between-population differentiation, as seasonal migration confound with dispersal15. In such cases, a high genetic resolution can offer insights into individual ancestries that distinguish seasonal migrators vs dispersers.In many instances, however, inferring genetic structure is far from trivial. Patterns of population differentiation may be difficult to detect for mobile organisms, as populations are homogenized by recurrent episodes of gene flow17 and experiencing high mutation rates that generate myriads of alleles. They accordingly remain popular markers to estimate gene flow and diversity among recently diverged populations ever since the late 1990s19. Also highly polymorphic, mitochondrial DNA (mtDNA) is more straightforward and cheaper to analyze, notably across evolutionary distant populations, and has accordingly been preferred by researchers interested in range-wide phylogeographic structure20. However, mtDNA faces inherent limitations with respect to its clonal nature and maternal mode of inheritance, which makes it more sensitive to selection21 and can bias the reconstruction of the demographic history of populations, especially when dispersal is sex-biased24. In recent years, molecular ecologists benefit from high-throughput sequencing technology to access unprecedented numbers of loci, as prepared by genomic libraries26. In particular, restriction-site associated DNA sequencing  have become a popular method to genotype hundreds to thousands single nucleotide polymorphisms (SNPs) across conspecific or interspecific populations for multiple applications, such as high-resolution phylogeography29 and population genetic studies of weakly structured species28. The number of alleles of a single microsatellite locus is much higher than that of SNPs, but microsatellite analyses rarely include more than 10–20 loci due to practical constraints. By generating several hundred times more loci, RAD-seq thus largely compensates for the lower per-locus diversity of SNPs to provide more powerful population genetic inferences, notably in situations when gene exchange is hard to apprehend. However, such improvement has not been satisfactorily quantified, since the few comparative studies have focused on species with relatively strong levels of population differentiation, where structure is already detected efficiently by microsatellites (reviewed by30).In theory, the accuracy of population genetic analyses should depend on the number of loci used in respect to their standing variation. Microsatellites combine the advantages of evolving neutrallyMiniopterus schreibersii. This species was once considered to extend from Western Europe to Australasia, but taxonomic changes have now restricted its range to the Western Palearctic, where it is mostly found around the Mediterranean Basin . Bats in general are models of choice to gauge the resolution of genetic markers. Their high mobility usually combined with female philopatry and sex-biased dispersal31 implies pervasive gene flow and cyto-nuclear discordances32, thus inducing substantial difficulties to retrieve clear signals of population structure from traditionally used loci. In this respect, M. schreibersii is a long-distance traveler33 that conducts fixed seasonal migrations between hibernacula, maternity roosts and mating sites by movements of 40–100 km on average, but up to several hundred kilometers35. Nevertheless, young or adult dispersal overall remain rare in this species, so regional rather than long-distance movements have been argued to contribute most of the genetic exchanges36. As a consequence, the composition of nursery and hibernation sites were shown to differ38, so individuals of independent origins could temporarily share the same sites.In this study, we assessed how much RAD-seq can clarify subtle patterns of population structure compared to microsatellites in one of Earth’s widespread mammals, the bent-winged bat 39, and microsatellite analyses did not detect meaningful geographic patterns of nuclear differentiation40. Both results were interpreted as the consequence of the biogeographic history of the species, namely the massive recolonization of Europe after the last ice age from a single refugium, presumably in Anatolia40. While this hypothesis has merit, such strong genetic homogeneity at the continental scale may equally reflect the lack of informativeness of conventional genetic markers to detect shallow levels of population differentiation, for instance, if refugial structure had been compromised by high levels of post-glacial gene flow in this mobile species. Likewise, these may overlook subtle genetic signals caused by the social organization of the species. Precise knowledge of the genetic diversity and genetic structure would also be relevant to guide conservation planning. Despite its wide distribution, M. schreibersii is facing dramatic declines in Europe since the mid-twentieth century, even being extirpated from several countries in recent years, to the point that it is presently considered Vulnerable by the IUCN Red List (VU A2c)41.Despite substantial sampling and genotyping efforts, previous studies reported little genetic structure across the vast range of the species. Mitochondrial analyses found a single mitochondrial clade, with closely related haplotypes shared all over the Mediterranean BasinM. schreibersii thus remains an open question, especially given the (lack of) geographic patterns retrieved from previous studies. Genomic analyses would thus be timely, and in turn offer an opportunity to assess the molecular resolution required to detect genetic structure when there is little. To this end, here we analyzed regional sets of population and individual samples across the western and Central European ranges of M. schreibersii with microsatellite loci and SNPs obtained from ddRAD-seq. The outcomes of both approaches were directly compared by quantitative  and qualitative (clustering assignment) measures. While RAD-seq is generally expected to provide more accurate estimates, it should be particularly more informative than microsatellites to detect phylogeographic and regional structure, even if populations frequently exchange genes and migratory individuals.How biogeographic history, social organization and recent declines have interacted with philopatry, regional dispersal and long-distance migration to shape the genetic structure of M. schreibersii were sampled from 19 localities covering seven European regions during spring and summer 2010, 2011 and 2012  following the manufacturer’s instructions except for the following particularities. Blood-soaked paper fragments (~ 10 mm in diameter) were cut in small pieces with sterile scissors, and incubated in 360 µL of ATL buffer at 90 °C for 15 min. After cooling, 40 µL of Proteinase K was added to each sample and left for overnight digestion at 56 °C. Elution was performed in 55 µL volumes and by incubating 15 min at 37 °C prior to centrifugation. This step was repeated a second time to maximize DNA yields. For a subset of individuals, additional DNA was extracted from the wing biopsy after rinsing the ethanol-preserved tissues by pure MilliQ water soaking (Millipore ®).43. Loci, primers, and amplification protocols are detailed in44. Amplicons were quality-checked on an agarose gel, typed on an ABI Prism 3100 genetic analyser (Applied Biosystems ®) and size-scored with GeneMapper (Applied Biosystems). Finally, we checked for large allelic drop out, stuttering and null alleles using Micro-Checker v2.2.345.Individuals were genotyped at 11 polymorphic microsatellite loci amplified in four multiplex PCRs46, as detailed in Supplementary File For genomic library preparation, extracted samples were first concentrated using a chloropane precipitation. We then prepared a ddRAD library modified from47. Low quality (Phred score below 10 averaged on 15 bp sliding windows) and monomorphic sequences were filtered out, with a minimum coverage of three and stacking up to 3% of divergence between reads.Sequences with low signal-to-noise ratio (< 0.6) were discarded using Illumina’s Chastity filter. In the absence of a reference genome, demultiplexing, stacking and cataloguing of reads was performed with the de-novo pipeline of STACKS 0.996IS48 outside the range of − 0.2 and 0.2 were removed with hierfstat49, since extreme heterozygote deficits are not expected in a diploid species with separate sexes.Custom R scripts were developed for additional filtering and SNP calling. First, loci with more than five SNPs were discarded in an effort to exclude repetitive elements, and a threshold of eight reads per genotype was applied. Second, tri-allelic genotypes, heterozygotes with a rare allele represented by less than 25% of the reads, and singleton were not considered. Third, SNPs were called as genotyped if sequenced in at least 70% of individuals. Finally, to exclude obvious outliers, SNPs with a Fhierfstat49 from standard population genetics parameters50. First, we computed observed heterozygosity (HO), expected heterozygosity , overall heterozygosity over populations (hT), allelic richness (aR), population specific FST (Beta51) and departure from Hardy–Weinberg (FIS). 95% Confidence Intervals (CI) for heterozygosities and F-statistics48 were estimated by bootstrapping 1000 times the variance components. Pearson correlations were used to compare estimates between marker sets, and to assess the influence of missing data on the RAD-seq estimates. To identify any outlier locus, we further investigated the relation between allele frequencies and observed heterozygosity for both marker sets by plotting HS and their 95% confidence intervals given allele frequency and global heterozygote deficiency, computed as HS = 2p(1 − p)(1 − fIT) ± 2[(2p(1 − p)(1 + fIT)/N]0.5.Genetic structure and diversity from the microsatellite and RAD-seq datasets were investigated at the population level using ST between populations48 were estimated and compared between marker sets by Mantel tests52, then used to test for isolation-by-distance (IBD53). Chord distances54 were computed (genet.dist function of hierfstat), translated in a neighbour-joining tree (bionj function of ape55). Furthermore, hierarchical analyses of genetic variance were carried out to test for the effects of countries and populations. To this aim, FST was partitioned between populations, within country (FSC), and between countries (FCT).Second, pairwise Fhierfstat (sexbias.test function56), which was compared between marker sets by a Pearson correlation.Third, we tested for sex-biased dispersal using the mAIc index implemented in indpca function of hierfstat50.Genetic structure among individual genotypes was first examined by Principal Component Analyses (PCA) on each marker set, using the snmf clustering algorithm implemented in LEA57 to estimate in how many clusters the dataset can be summarized, and compute individual ancestries of each individual among these clusters. For each marker set, chains were run for K = 1–7 clusters, with 20 repetitions for each K, and blinding 10% of the data for the cross-entropy estimation (function snmf). Most likely Ks are reflected by low cross-entropy values. The alpha parameter was kept to the default 100 (as recommended by the authors), especially as it did not affect the results in preliminary runs. To appreciate the influence of missing data on the RAD-seq dataset, runs were also performed on a reduced dataset based only on individuals featuring above 70% of SNP matrix completeness (n = 172). Finally, we further explored how the number of loci influenced the retrieved patterns of genetic structure by repeating the admixture analysis on randomly selected subsets of 3,000, 2,000, 1,000, 500, 200 and 100 SNPs.Second, we applied the M. schreibersii across seven European countries , a mean expected heterozygosity HS of 0.557 (0.395–0.694) and an overall heterozygosity HT of 0.588 (0.418–0.734). These values are much larger than the diversity measured at bi-allelic SNPs, with a mean HO of 0.122 (0.119–0.126), mean HS of 0.129 (0.125–0.133) and mean HT of 0.139 (0.134–0.143). Departure from Hardy Weinberg equilibrium overlapped between marker sets . Most SNPs and microsatellite alleles show good concordance between observed and expected heterozygosities  and population specific FST  , as expected since ar co-varies with hs. In contrast, the relationships were not significant for fis and ho  was stronger when estimated from SNPs (mean FST = 0.068 [0.065–0.071]) than from microsatellites (mean FST = 0.053 [0.041–0.066]). There was a significant correlation between microsatellite- and SNPs-based FST estimates .fct) than between sub-populations within countries (fsc), especially when estimated from SNPs: for microsatellites, fsc was 0.023 (0.013–0.034) and fct was 0.035 (0.026–0.043), whereas for SNPs, fsc was 0.019 (0.017–0.020) and fct was 0.058 (0.056–0.061).Accordingly, analyses of genetic variance revealed stronger differentiation between countries . The corrected mAIc for microsatellites and SNPs are strongly correlated .Both datasets showed no evidence for sex-biased dispersal , depending on the number of retained markers and the complexity of the clustering scheme (number of K groups) Fig. . With laM. schreibersii , the SNPs dataset recovered clear patterns of genetic structure across the sampled range of ii Figs. , 5, 6, 7Detailed inspections of the admixture runs with up to seven groups revealed remarkable substructure among the main Portuguese, Italian and Croatian clusters that allow tracking individual movements at the regional level. In Portugal, bats caught at loc. 3 and 4 differ genetically , varied greatly among populations, being generally higher in Portugal, northwestern Spain and Croatia  vs many bi-allelic loci (SNPs obtained by RAD-seq).Flying vertebrates are expected to feature shallow genetic differentiation between populations due to their high movement capabilitiesfST estimates across the European range of M. schreibersii, namely 0.05 (microsatellites) or 0.07 (SNPs) on average. This is in accordance with previous microsatellite genotyping that found little genetic differentiation across the range of the species40, as well as the fact that a single mitochondrial lineage inhabits Europe39. As these studies concluded, the lack of phylogenetic divergence between populations separated by thousands of kilometers, and the marked isolation-by-distance, suggest high connectivity.Both sets of markers recovered low 40. Under this scenario, a single genetic cluster and a westward longitudinal gradient of genetic variation would have been expected across the whole continent . Whether the glacial ranges of M. schreibersii also encompassed Mediterranean Europe, in addition to Anatolia, thus remains an open question. In fact, the structure we identified in Europe would even be consistent with distinct historical refugia across the Iberian, Apennine and Balkan Peninsula, perhaps subdivided into micro-refugia . In this respect, the puzzling ancestry of Slovakian bats could reflect recent admixture between the Croatian group and a gene pool that we have not sampled i.e., from another separate refugium, for instance, Anatolia. The last lines on the biogeography of M. schreibersii are thus yet to be written. A genomic survey encompassing both European and extra-European populations to thoroughly infer range-wide patterns of genetic diversity, structure, and admixture, perhaps combined with environmental niche reconstruction to track habitats suitable for the species during the last glacial maximum, will hold key to disentangle among the one refugium vs several refugia hypotheses.Unlike previous studies, however, we did recover genetic structure across Europe with genome-wide SNPs. We also found similar levels of diversity between populations, especially between the eastern- and westernmost ones . Both results are somewhat surprising if one assumes that the species post-glacially expanded across Europe from a single Anatolian refugium—the currently accepted biogeographic scenario, based on higher mitochondrial and microsatellite diversity in AnatoliaNyctalus leisleri60 or Plecotus austriacus61. Like M. schreibersii, European bats in general show little phylogeographic structure63, or sometimes recent geographic isolation resulting from the last glacial stage, as in Rhinolophus ferrumequinum64 and Rhinolophus hipposideros65. Yet, the lack of clear genetic structure between candidate refugial regions does not necessarily imply a single refugium scenario, as here previously assumed for M. schreibersii40, as well as in other species, e.g., Myotis bechsteinii66. In mobile organisms, genetic signals for multiple refugia  can quickly disappear in the event of gene flow and lineage fusion67, and become undetectable with few bi-parentally inherited microsatellite loci. Long-lasting signals may persist in the mitochondrion, but only if females are more philopatric than males. In a similar fashion, multiple refugia exist in the European Barn Owl —a fast-dispersing bird with a similar circum-Mediterranean distribution—but it was likewise only retrieved from genomic data, namely whole-genome sequencing59, and not microsatellites68. Classic biogeographic paradigms characteristic of terrestrial vertebrates, such as the long-term persistence in separate Mediterranean refugia70 and their regional differentiation in refugia-within-refugia71 might thus apply to bats and birds even if microsatellite studies have so far suggested otherwise. That said, some widespread Holarctic bat species may truly be genetically homogenous. For instance, the north-American Myotis lucifugus lacks population differentiation, as measured from both conventional (microsatellites + mtDNA72) and genomic markers .Suitable glacial habitats were modelled in southern Europe for other species of bats with roughly similar distributions, e.g., M. schreibersii. In bats, mating and breeding colonies are often spatially separated75, and their average genetic diversity and relatedness vary accordingly66. In addition, females are usually the philopatric sex, and males the dispersing sex, which should affect mitochondrial vs nuclear patterns of genetic structure31.Despite the relatively weak range-wide differentiation, the high-resolution offered by our RAD-seq dataset recovered regional signals of population sub-structuring, which can be interpreted in the light of the social habits of M. schreibersii, ringing data have suggested that both males and females were philopatric36, and we also recovered no evidence for sex-biased dispersal. Male-biased dispersal was however detected by a regional population genetic study focusing on the Portuguese colonies38. The discrepancy probably lies in the larger geographic scale of our study compared to the latter: sex-biased dispersal can only be retrieved if the dataset contains a fair amount of dispersers56, which are obviously in lower proportions at the continental compared to the regional scale, especially if dispersal remains rare overall.In M. schreibersii is a keen seasonal migrator (moving a lot between colonies), but a weak disperser (exchanging little genes between them)36. Hence, the social organization of the species momentarily shapes the genetic diversity of its populations, which may differ between nursing, mating and hibernating sites. The factors triggering genome-wide divergence between co-occurring nursing individuals remain elusive, and may include isolation-by-distance, assortative mating, or a meta-population structure—which has been documented in bats77. More insights will come from assessing fine-scale geographic patterns of genetic diversity from the mating sites i.e., the “true” origins of individuals, and test whether these are genetically isolated.Furthermore, we detected syntopic individuals with unrelated ancestries in several nursing sites of Portugal (loc. 1–2), Italy (loc. 12), and Croatia (loc. 15–16), yet with little signs of local admixture—which would have been flagged by intermediate ancestry coefficients. These sites thus act as “regional hubs” where individuals of various origins temporarily meet yet remain genetically differentiated. Such observations are consistent with the idea that vs genomics methods to infer population diversity and structure, especially in the context of conservation81. In their synthesis, Sunde et al.30 concluded that RAD-seq performed as well or better than microsatellites, as similar trends of clustering and heterozygosity were always recovered from both types of markers  were much clearer when inferred from SNPs . Therefore, our study extends the conclusions of Sunde et al.30 that SNPs provide a significant upgrade to microsatellite-based population genetics, even more so in mobile organisms with shallow genetic structure, as well as for tracking individual movements.Unlike previous comparative studies, here the generally low genetic differentiation among European populations of us Figs. , 2, 3, 4Ps Figs. . This re79 reported gradual improvements with different filtering stringencies that increased their datasets from ~ 200 to ~ 25′000 SNPs . Our sub-setting analyses largely agrees with their conclusions. While our 100–200 SNPs datasets were mostly uninformative, 500 SNPs  still recovered most of the shallow structure of M. schreibersii, and at least 1,000 SNPs were required to investigate the regional substructure 84. As previously recommended36, the genetic differentiation documented at the regional scale calls for protecting all the sites used by the species, both to ensure regional connectivity between the hubs visited by seasonal migrants and to preserve the genetic uniqueness of the different demes, as it might convey components of local adaptation. Moreover, some of the most isolated sites in Portugal (loc. 4) and France (loc. 9) show the lowest genetic variation, which may reflect genetic bottlenecks ensuing the population collapses from the 2000s83. These populations should thus remain under constant care, especially if their eroded genetic diversity negatively affect fitness85. Besides, recovery programs have proven very efficient in M. schreibersii86. Finally, the genetic groups and individual movements identified inform on the risk assessment of future disease outbreaks, in the context of the possible re-emergence of the Lloviu virus, which has been re-detected since 2016 in an Hungarian colony87 and was shown potential to infect human cells 88. The spreading may be fast within regions—where bat populations are either panmictic, or in close contact during nursing—but could be slower at the continental scale given the structuration between European countries.Our study provides applied lessons for the conservation of 89. In a similar fashion, the ongoing fragmentation of M. schreibersii’s range could have contributed to promote the genetic differentiation between the Portuguese, Spanish, French, Swiss and Croatian populations. We argue that the lack of resolution offered by traditional population genetics potentially hamper the identification of subtle patterns of genetic structure in phylogeographically shallow taxa, and that the situation of the declining M. schreibersii might be more common that previously assumed.Weak genetic differentiation at the global scale despite rare dispersal and marked structure at the local scale may appear counter-intuitive, yet such pattern is not unheard of among geographically-scattered species. An analogous situation was documented in the common hippopotamus, which expanded across Africa in a single wave (homogenizing its rich genetic diversity), before contemporary habitat fragmentation created barriers to dispersal and drove genetic bottlenecksSupplementary Information.


The bubble during its collapse emits shockwaves that under certain conditions converge to a single point where the remaining gas phase is driven to a shockwave-intensified collapse. We resolve the conditions under which this self-focusing enhances the collapse and damages the solid. High-speed imaging of bubble and shock wave dynamics at sub-picosecond exposure times is correlated to the shockwaves recorded with large bandwidth hydrophones. The material damage from several metallic materials is detected in situ and quantified ex-situ via scanning electron microscopy and confocal profilometry. With this knowledge, approaches to mitigate cavitation erosion or to even enhance the energy focusing are within reach.The ability of cavitation bubbles to effectively focus energy is made responsible for cavitation erosion, traumatic brain injury, and even for catalyse chemical reactions. Yet, the mechanism through which material is eroded remains vague, and the extremely fast and localized dynamics that lead to material damage has not been resolved. Here, we reveal the decisive mechanism that leads to energy focusing during the non-spherical collapse of cavitation bubbles and eventually results to the erosion of hardened metals. We show that a single cavitation bubble at ambient pressure close to a metal surface causes erosion only if a  Such a bubble will collapse spherically and focus the liquid’s kinetic energy towards the bubble center Cavitation erosion has also been attributed to the shockwaves emitted during collapse and their interaction with the boundary. In experiments, the pressures of the shockwave were measured with hydrophones and their fronts were imaged based on the density dependent refractive index of water Computational fluid dynamics offers a route to obtain the pressure loading of the boundary from the jet impact and collapse, and thus to relate it to the material properties such as its yield strength. Investigations at intermediate stand-offs from the bubble to the wall suggest that peak pressures from the jet impact and torus-shaped collapse on the boundary are of similar strength, while in many scenarios the pressure of the torus collapse exceeds that of the jet impact Here we reveal that instead of axisymmetric shock focusing or jet impact reported previously, it is the non-axisymmetric self-focusing of energy that results to erosion. Here already a single bubble collapse at atmospheric pressure is sufficient to erode even hard metallic surfaces. We therefore suggest, that the reported non-axisymmetric self-focusing mechanism is the main cause of cavitation erosion in general.2N identical bubbles are generated sequentially. The location of damage surface is detected in situ relative to the bubble dynamics and combined with ex-situ confocal as well as scanning electron microscopy (SEM).We experimentally study the surface damage from the collapse of single, laser-induced cavitation bubbles by high speed imaging of the bubble dynamics and shadowgraphy of the shockwave fronts, complemented with measurements of acoustic transients. At the same position close to a solid, Erosion tests are conducted in the experimental setup sketched in 3 and polished by hand. Vickers hardness was measured for aluminium alloy, copper brass and the stainless steel as 65HV5, 72HV5 and 167HV5, respectively. The silver sample is a single crystal , fcc, dimensions 15 mm × 6 mm × 1 mm, Young’s modulus The shockwaves emitted during the bubble collapse are visualized with shadowgraphy. We freeze the bubble dynamics and the shockwave propagation in time by illuminating the scene with an expanded laser pulse train  and the fiber because of its directive sensitivity. Therefore the optic hydrophone is moved together with the sample. A second important detail is the waiting time between successive bubble generations, thus to allow gaseous fragments from one laser-generated bubble to move away and/or dissolve such that they do not interfere with the dynamics of the following bubble. Here we chose delays longer than E scales with f, we take the Nyquist frequency of the rise time of the pressure transients measured with the high bandwidth fibre optical hydrophone, which is about The bubble dynamics depends delicately on the stand-off. In particular in the small stand-off regime, already a few micrometers decide if the collapse dynamics result in the formation of the needle-jet sion see a. Rmax ins-1 see c. Combin33.1Damage Morphology The damage on a silver single-crystal surface as function of the stand-off distance When the bubble is generated very close to the solid surface  the cap collapse, corresponding to 2) the needle-jet piercing with the splashing after impact on the solid (2) the needle jet is captured during its passage through the vapour phase revealing a fragmented tip. Possible scenarios causing this atomization could be a destabilization by the hypersonic needle-jet speed 2. Its propagation distance is estimated as The last frame in 3), we study the collapse from the top view, i.e. through a transparent glass sample, sketched in Before discussing the events leading to the strong shockwave formation in Consequently, bubble fragments on top of the bubble at the former cap position appear  a laser pulse is focused directly onto a submerged substrate and the material is ablated through plasma generation In laser lithotripsy an optical fibre is used to deliver an infrared laser pulse to fragment and erode kidney stones Recently, advanced strategies of fluid structure interaction have been developed that couple single bubble dynamics and their violent impact on boundaries with the aim to predict cavitation erosion A reliable technique to detect erosive cavitation from acoustic measurements is currently not available. Even though cavitation noise has been studied and the occurrence of cavitation can be well detected from broadband noise or from a significant energy content in the sub- and ultraharmonic frequency spectrum, the acoustic assessment of the erosiveness of cavitation has only been partly successful The erosiveness of cavitation is drastically decreased when the regular jet threads the bubble. This is the case for intermediate stand-offs (The regular jet impact itself is not responsible for erosion, even not through fatigue effects in any of the metallic materials tested.The damage in the intermediate stand-off can clearly be attributed to the second collapse which is in accordance with previous works 5Cavitation bubbles are only erosive if their first collapse occurs very close to the surface, i.e. only for The self-focusing effect here is strongest around The regular jet with its velocity of about The results suggest a strategy to mitigate cavitation erosion: for a bubble collapsing at a wall, the regular jet must be stimulated to fragment the bubble. This could be done by appropriate surface structuring or introducing appropriate pressure gradients, for example via sonification. On the other hand, the findings imply strategies to intensify the collapse, as for example to achieve a more efficient nanoparticle production, laser-assisted material machining or for sonochemical reactions with more extreme conditions in the bubble interior. Here a small controlled asymmetry, purposefully introduced could be a promising strategy to achieve the most extreme energy concentration. Shock-resolving 3-dimensional simulations seem a natural way to understand which kind of asymmetries could lead to enhancing or prevention of cavitation erosion.FR designed and conducted the experiments and analysed the data, FR and CDO contributed to the interpretation of the data. CD contributed to surface analysis and performed the sample preparation. FR wrote the manuscript with input from all authors.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


The genetic diversities of mammalian tick-borne flaviviruses are poorly understood. We used next-generation sequencing (NGS) to deep sequence different viruses and strains belonging to this group of flaviviruses, including Central European tick-borne encephalitis virus (TBEV-Eur), Far Eastern TBEV (TBEV-FE), Langat (LGTV), Powassan (POWV), Deer Tick (DTV), Kyasanur Forest Disease (KFDV), Alkhurma hemorrhagic fever (AHFV), and Omsk hemorrhagic fever (OHFV) viruses. DTV, AHFV, and KFDV had the lowest genetic diversity, while POWV strains LEIV-5530 and LB, OHFV, TBEV-Eur, and TBEV-FE had higher genetic diversities. These findings are compatible with the phylogenetic relationships between the viruses. For DTV and POWV, the amount of genetic diversity could be explained by the number of tick vector species and amplification hosts each virus can occupy, with low diversity DTV having a more limited vector and host pool, while POWV with higher genetic diversities has been isolated from different tick species and mammals. It is speculated that high genetic diversity may contribute to the survival of the virus as it encounters these different environments. Flavivirus of the family Flaviviridae that are transmitted by ticks , and a West Nile virus strain NY99 previously sequenced in the author’s laboratory, as an outgroup . OverallGenetic diversity within the viral RNA populationNGS was used to investigate the genetic diversity of each MTBF member in this study in terms of Shannon entropy and single nucleotide variants (SNVs) . The depp < 0.0001), and KFDV differed from most viruses except the two TBEV strains (p > 0.9999) (p < 0.0001). LGTV/TP21_I differed from LGTV/TP21_II and LGTV/TP21_III  . The statistics are summarized in Interestingly, there were differences between the Shannon entropy of particular viruses. AHFV was different from every other virus in this study ( 0.9999) . LGT, POctively) . LGTV/TPIn terms of SNVs, there was considerable variability between the viruses. POWV/LEIV-5530 had 32 SNVs ranging from 1.0–33%, and POWV/LB had 29 SNVs ranging from 1.1–44% . In compThis study has compared the genetic diversity of different members of the MTBF group by NGS. The analyses of the consensus sequences obtained in this study were very closely related to the genomic sequences reported in the literature and their genetic relationships, giving confidence to the analysis of genetic diversity . NGS revThe results from the different POWV and DTV samples suggest that genetic diversity within each strain remains consistent within the constraints of the limited passage histories studied, but the LGTV/TP21 with an additional passage in LLC-MK-2 cells (LGTV/TP21_I) was statistically different from the other two LGTV/TP21 viruses sequenced. However, it is difficult to identify whether those additional passages caused the difference in genetic diversity or there are other factors involved. I. scapularis ticks only, while POWV has been isolated from I. marxi, I. cookei, and I. spinipalpis in North America [Despite DTV being a genotype of POWV , the DTV America ,32, but Interestingly, the DTV/IPS-001 and DTV/NPS001 strains share 24 of 25 mutations detected , and theIn conclusion, these results provide one of the first reports on the differences and similarities of the genetic diversity across a wide range of MTBFs, some of which had not been previously subjected to deep sequencing. The results suggest that there may be a correlation between the phylogenetic grouping and the levels of genetic diversity observed in these viruses. However, additional studies would be needed to determine the genetic diversity inside and outside of the different hosts that tick-borne viruses occupy to further understand the evolution of the MTBFs .


Flower phenotypes evolve to attract pollinators and to ensure efficient pollen transfer to and from the bodies of pollinators or, in self‐compatible bisexual flowers, between anthers and stigmas. If functionally interacting traits are genetically correlated, response to selection may be subject to genetic constraints. Genetic constraints can be assessed by quantifying standing genetic variation in (multivariate) phenotypic traits and by asking how much the available variation is reduced under specific assumptions about phenotypic selection on functionally interacting and genetically correlated traits.Dalechampia blossoms. First, we used data from a greenhouse crossing design to estimate the G matrix for traits representing the relative positions of male and female sexual organs (anthers and stigmas) and used the G matrix to ask how genetic variation is distributed in multivariate space. To assess the evolutionary importance of genetic constraints, we related standing genetic variation across phenotypic space to evolutionary divergence of population and species in the same phenotypic directions.We evaluated multivariate evolvability and potential genetic constraints underlying the evolution of the three‐dimensional structure of Evolvabilities varied substantially across phenotype space, suggesting that certain traits or trait combinations may be subject to strong genetic constraint. Traits involved functionally in flower‐pollinator fit and autonomous selfing exhibited considerable independent evolutionary potential, but population and species divergence tended to occur in phenotypic directions associated with greater‐than‐average evolvability.These results are consistent with the hypothesis that genetic constraints can hamper joint trait evolution towards optimum flower‐pollinator fit and optimum self‐pollination rates. Evolution of complex phenotypes is commonly governed by multiple conflicting selection pressures interacting with genetic constraints . Studies of G matrices for complex phenotypes have revealed that genetic variance is often unevenly distributed across phenotype space, so that some phenotypic axes (trait combinations) are associated with above‐average evolvability, while others exhibit little or no evolvability . We then used the G matrix and the multivariate evolvability framework of Hansen and Houle  has been a long‐term model system for investigating pollinator‐mediated floral evolution. The woody vine D. scandens L. s.l. is typical of the genus in having unisexual male and female flowers aggregated into functionally bisexual blossom inflorescences  for gland–stigma distance, gland–anther distance, and anther–stigma distance, three key traits that jointly describe the relative positions of male and female sexual organs , plants (j), dates (k), and individual blossoms (l). To estimate the G matrix (G), the “animal”‐level random effect was distributed as a~N, where A is the additive relatedness matrix derived from the breeding design, and ⊗ is the Kronecker product , measurement dates (d), and blossoms within plants (q). We sampled the posterior distribution for 750,000 iterations with a transient of 250,000 iterations discarded and a thinning interval of 500 and confirmed convergence by evaluating posterior trace plots and confirming effective sample sizes close to the expected 1000.To estimate the β is defined as the predicted evolutionary response to selection in the direction of β. To quantify multivariate constraints arising from the quantitative‐genetic architecture of complex phenotypes as represented by the genetic variance matrix G, Hansen et al. (β when other defined phenotypic traits are held constant (as when these are under stabilizing selection). In the present study, quantifying conditional evolvabilities allowed us to explicitly evaluate, for example, how much the realized evolvability of anther–stigma distance is reduced assuming stabilizing selection on the flower‐pollinator fit traits . The proportion of genetic variance available while conditioning on the constraining traits is referred to as autonomy.Hansen and colleagues  of the eigenvalues, and the mean of the univariate evolvabilities .We used functions from the evolvability R package , population divergence, and species divergence following the approach of Bolstad et al. , populations (j), plants (k) and individual blossoms (l). The population‐level random effect estimates the variance matrix DP for population‐mean phenotypes across populations. The phenotypic measurements were ln‐transformed before analysis, and the estimated variances and covariances are therefore on a proportional scale comparable to the within‐population evolvabilities.To assess the role of genetic constraint in the evolution of floral architecture in d et al. . At the DS, we fit a similar model to field measurements from 43 populations of 11 Dalechampia species , and the D matrices describe proportional variance among populations or species. The genetic‐constraints hypothesis predicts a positive relationship between proportional evolutionary divergence and evolvability  of 2.59% can be interpreted as the expected proportional response to an episode of unit‐strength selection and translates into an evolutionary doubling‐time of t2 = ln(2)/0.0259 = 26.8 generations under unit strength selection.Univariate evolvabilities differed markedly among the three original traits Table , and theThe moderately strong genetic correlations between the three focal traits translated into a median autonomy of 53.3% Table , which mExploring patterns of evolvability across randomly chosen directions in phenotypic space Figure  revealedComparing the extent of population divergence among the original traits and among directions in phenotypic space revealed an overall positive relationship, and the most evolvable focal trait (anther–stigma distance) has diverged the most among populations Figure . DirectiWhen focusing on the divergence of species and thus extending the time‐scale and extent of divergence, the positive relationships between divergence and evolvability remained. However, at the species level, both pollinator‐fit traits have diverged to approximately equal extents, despite greater evolvability of gland–stigma distance than gland–anther distance Figure .Dalechampia blossom traits involved in flower‐pollinator fit and autonomous selfing exhibit appreciable independent evolutionary potential, but also that populations and species have diverged to a greater extent in those phenotypic directions associated with greater multivariate evolvability. The latter result is consistent with the hypothesis that joint trait evolution toward optimum flower–pollinator fit and optimum self‐pollination rate is subject to genetic constraints, thus possibly providing a partial explanation for the observed distribution of trait values across the genus . This result confirms the unusually high evolvability of herkogamy  is consistent with a previous literature survey . One way forward would thus be to combine estimates of population divergence, (multiple) G matrices, and multiple selection estimates  of Dalechampia taxa included in the analysis of species divergence.Click here for additional data file.


N-nitroso compounds with carcinogenic, mutagenic and teratogenic properties. These compounds could be found at certain levels in fermented sausages. Fermented sausages are considered to be a suitable environment for nitrosamine formation due to acid formation and reactions such as proteolysis and lipolysis during ripening. However, lactic acid bacteria (spontaneous or starter culture), which constitute the dominant microbiota, contribute significantly to nitrosamine reduction by reducing the amount of residual nitrite through nitrite degradation, and pH decrease has an important effect on the residual nitrite amount as well. These bacteria also play an indirect role in nitrosamine reduction by suppressing the growth of bacteria that form precursors such as biogenic amines. In recent years, research interest has focused on the degradation or metabolization of nitrosamines by lactic acid bacteria. The mechanism by which these effects are seen has not been fully understood yet. In this study, the roles of lactic acid bacteria on nitrosamine formation and their indirect or direct effects on reduction of volatile nitrosamines are discussed.Nitrosamines are  Meat plays an important role in human nutrition and is an important source of high value biological protein, minerals such as iron, zinc, selenium, and B group vitamins such as B12 ,4,5.Fermentation is one of the oldest and most widely used methods in food preservation, and it has an important place in the processing and preservation of meat. Fermented meat products are divided into two main groups: fermented sausages and meat products made from whole pieces. In fermented sausages, the expression “sausage ripening” is used for the changes that occur during the period from stuffing to the final product, and consists of two stages; fermentation (mainly lactic acid formation) and ageing  . The latw), degree of chopping of meat and fat, and geographical region [Fermented sausages are meat products obtained by mixing minced meat and fat in a meat grinder or cutter with various spices, sugar and other additives, filling the mix in natural or artificial intestines and ripening at a certain temperature and relative humidity . The chal region . For insl region . The watl region .3) and/or nitrite (NO2) are added to fermented sausages as a curing agent. Nitrite is preferred for rapidly ripened fermented, nitrate and/or nitrite is preferred for slow ripened fermented sausages. Although nitrate is an important source of nitrite in such products ripened for a long time period, it must be reduced to nitrite in order for the expected effects from this curing agent to occur [w and pH, nitrite is considered an important hurdle effect in fermented meat products. Nitrite plays an important role in the formation of the characteristic color, development of flavor and delay of oxidation. Nitrite is also effective in inhibiting foodborne pathogens such as Listeria monocytogenes and Salmonella in fermented sausages [Nitrate  and N-nitrozopyrrolidine (NPYR) were found in fried bacon. Most studies on nitrosamines were conducted in the 1970s and early 1980s, and such preventive measures as limiting the level of nitrites added and using antioxidants such as ascorbate in the production of meat products were highlighted to control this contamination [N-nitrosodimethylamine (NDMA), N-nitrozopyrrolidine (NPYR), and N-nitrozopiperidine (NPIP) are widely identified in fermented sausages [N-nitrosomorpholine (NMOR), N-Nitrosodiethylamine (NDEA), N-Nitrosodibutylamine (NDBA), N-nitrosomethylethylamine (NMEA) are some other nitrosamines that can be seen in fermented sausages [products . Concernmination . pH and mination ,21. Fermmination . On the mination ,24,25. Smination . N-nitrosausages . NDMA issausages . Besidessausages ,21.Various strategies have been developed to reduce the formation of nitrosamines. Many studies have been conducted on the possibilities of using compounds such as ascorbic acid and polyphenols as inhibitors in the formation of nitrosamines ,28,29,30Traditional dry fermented sausages rely on spontaneous fermentation by indigenous microbiota that can originate from the raw material or from the environment. Such microbiota is called “house flora” and is composed of technologically important microorganisms during ripening, as well as of spoilage microorganisms that can negatively affect the properties of the final product, and may also include some pathogenic microorganisms ,41. ExceLatilactobacillus sakei, L. Latilactobacillus curvatus, Lactiplantibacillus plantarum are the most commonly identified species [Pediococcus acidilactici, P. pentosaceus, Lactiplantibacillus pentosus and L. plantarum, which are used as starter cultures in fermented meat products, are isolated less commonly when compared to L. sakei or L. curvatus, due to the fact that their competitiveness is low in the majority of traditionally-produced fermented sausages. These species cause considerable acidification in the first days of the fermentation, but they may not be able to prevent the development of non-starter lactic acid bacteria that may demonstrate undesirable effects in the final product. On the other hand, L. plantarum may also cause high acidity in the final product [Pediococcus is preferred to lactobacilli in those products which are rapidly ripened at high temperatures. Moreover, as the ripening period proceeds, the number of Pediococcus decreases [Lactic acid bacteria and Gram (+) catalase positive cocci are two groups of microorganisms that are technologically important during the fermentation and ripening of fermented sausages. Among the identified lactic acid bacteria,  species ,44,45,46 product . Pediocoecreases .Lactobacillus and Pediococcus species are used as lactic starter cultures in fermented meat products. L. sakei and L. curvatus species show good growth at fermentation temperatures of 20–24 °C and maintain their vitality significantly during ripening. L. plantarum and Pediococcus spp dominate the environment at higher fermentation temperatures [Listeria monocytogenes, Staphylococcus aureus, and Salmonella [eratures . The moseratures . The pH eratures ,13. The lmonella ,50,51.N-nitrosamines, which are formed by the electrophilic substitution reaction between the nitrozonium cation (NO+) provided by the nitrosation agent (Y-NO) and the amine nitrogen, are compounds associated with carcinogenic, mutagenic and teratogenic properties [+, which is necessary for the nitrosation reaction [N-nitrosamine formation may occur more easily in dry fermented sausages as the pH of the product approaches the optimum pH (pH 3.5) of the nitrosation reaction [The pH drop caused by lactic acid bacteria is also an important factor in the conversion of nitrite to nitric oxide. As the pH of the meat decreases, the concentration of nitrous acid increases, and therefore the nitrite concentration changes as a function of pH level . Nitriteoperties ,56. The operties ,58. The reaction . In genereaction . It was reaction ,60. Indereaction .Lipolysis, lipid oxidation and proteolysis occurring during ripening in fermented sausages are important phenomena for the flavor and aroma ,62. ProtL. sakei,L. curvatus and L. plantarum have several peptidase activities such as leucine and aminopeptidase [Lactic acid bacteria show low proteolytic activity, but the pH decrease caused by these bacteria contributes to proteolysis ,67. On teptidase ,69,70,71eptidase . The moseptidase . Putresceptidase . Lysine eptidase ,74,75. Oeptidase ,59. The eptidase . Howevereptidase ,77.N-nitrosodiethylamine (NDEA), N-nitrosodimethylamine (NDMA), N-nitrosopiperidine (NPIP), N-nitrozopyrrolidine (NPYR), N-nitrosodibutylamine (NDBA), N-nitrosomorpholine (NMOR), N-nitrozodipropylamine (NDPA), and N-nitrosodibenzylamine (NDBzA) [Nitrosamines are divided into two groups as volatile and non-volatile. Volatile nitrosamines are relatively nonpolar and low molecular weight compounds . Volatil (NDBzA) .N-nitrosodiphenylamine (NDPhA), N-nitrosomethylaniline (NMA), N-nitroso-2-methyl-thiazolidine-4-carboxylic acid (NMTCA), N-nitrosoproline, N-nitrosohydroxyproline, N-nitrososarcosine, N-nitrosothiazolidine, N-nitrosothiazolidine-4-carboxylic acid, N-nitrozooxazolidine-4-carboxylic acid, N-nitroso-5-methyloxazoldine-4-carboxylic acid, and N-nitroso-2-(hydroxymethyl) thiazolidine-4-carboxylic acid [Non-volatile nitrosamines are lic acid .w value of the final product are effective in this variation [In cured meat products, the nitrosamine level can vary significantly depending on the product and type of nitrosamine. While values lower than 5 μg/kg are usually detected in these products, nitrosamine level may be as high as 20 μg/kg. Nitrosamine content in fermented sausages, which are cured meat products, varies significantly ,54. Factariation . NDEA, wariation . In lateariation ,31,81. Nariation . Anotherariation ,82,83,84ariation ,28,81,85ariation . Anotherw values of fermented sausages indirectly affect the formation of NDMA through affecting the growth of some microorganisms with aminoacid decarboxylase activity [Enterobactericeaea and micrococci/staphylococci) with this activity [The level of NDMA, which is one of the commonly determined nitrosamines in fermented sausages, varies quite significantly. The precursor of NDMA is dimethylamine, a secondary amine. Another precursor of NDMA is putrescine. Fermented sausages are protein-rich foods, and as a result of proteolysis during ripening, amines are formed by endogenous or microbial enzymes, which may cause an increase in NDMA. In addition, protein oxidation can increase the amine content in these products, which are complex food systems . Furtheractivity . While tactivity . One of activity ,38,72. Hactivity . NDMA leactivity ,81,90,91activity ,91,92,93activity . On the activity   since it contains piperine and piperidine . NPIP waNPYR is one of the nitrosamines frequently detected in fermented sausages as NDMA. The major source of this nitrosamine is pyrrolidine. Many spices are also good sources of this compound. In addition, putrescine is also effective in the formation of NPYR . While mBiogenic amines, which are formed by bacterial decarboxylation of free amino acids in fermented sausages, can be indirectly involved in the formation of nitrosamines. Studies have shown that some biogenic amines can play a precursor role ,94,95,96Enterobacteriaceae family and Pseudomonas spp are known as major producers of cadaverine, histamine and putrescine [Enterobacteriaceae is inhibited and thus the formation of biogenic amines is limited [Enterobacteriaceae. This situation may also be evaluated as an indicator of low raw material quality and/or hygienic and technological rules not being followed during production [Enterobacteriaceae family members isolated from fermented sausages [Enterobacteriaceae decreases as the ripening period progresses [Micrococci and Staphylococci with decarboxylase activity is prevented by acidification during fermentation. These microorganisms are technologically important due to aroma formation, nitrate reductase activity and catalase activities in fermented sausages. Therefore, Staphylococcus xylosus, S. carnosus, Kocuria varians are added as a starter culture together with lactic acid bacteria in fermented sausages (6). However, micrococci and CNS to be used as starter cultures should also be tested for decarboxylase activity.Both Gram (−) and Gram (+) bacteria that are spontaneously present in fermented sausages can form biogenic amines. Members of the trescine . In ferm limited . Very hioduction . Histidisausages . In fermogresses ,43,75. SLactobacillus number is reported to have a significant impact on histamine formation [Carnobacterium, Latilactobacillus curvatus, and L. plantarum, Micrococcaceae and Latilactobacillus sake have been reported to play no role in tyramine formation [Enterococcus faecalis and E. faecium species, which belong to the lactic acid bacteria group, also produce high levels of tyramine. L. curvatus strains are reported to play a role in the formation of phenylethylamine, tryptamine, putrescine and cadaverine as well as tyramine [L. sakei and Pediococus pentosaceus inhibit the formation of biogenic amines [Lactiplantibacillus pentosus increases the competitiveness of the desired microbiota in dry fermented sausage production and also contributes to nitrosamine reduction by inhibiting the growth of microorganisms with decarboxylase activity and nitrate reductase activity [Biogenic amine levels in fermented products vary greatly depending on the raw material, fermentation conditions and microbiota. The literature is ripe with studies on the occurrence of biogenic amines in fermented meat products. Tyramine, histamine, phenylethylamine, tryptamine, putrescine, cadaverine, spermine and spermidine have been detected in a large number of analyzed products ,109,110.ormation ,100,111.ormation . It is styramine . Yet, soc amines ,114,115.activity .N-nitrosopyrrolidine (NPYR), and cadaverine or piperidine may play a role in the formation of NPIP [It was stated that putrescine, spermidine and spermine, which are biogenic amines determined in fermented sausages, can be effective in the formation of NPYR . In anot of NPIP . Cadaver of NPIP ,74,75. O of NPIP ,18.The nitrite level of meat products is an important factor in nitrosamine formation . Therefo2 or N2O through these enzymes under anaerobic conditions and reduce the residual nitrite level [Lactiplantibacillus plantarum, which has nitrite and nitrate reductase activity, reduced the amount of residual nitrite [Latilactobacillus sakei was used as starter culture [L. plantarum CMRC6 and L. sakei CMRC15 strains each have very good nitrite reductase capacity in a study [+3 in metmyoglobin to Fe+2 in deoxymyoglobin in cured meats (pH: 5.0–6.0) [The decrease in pH during fermentation in fermented sausages accelerates the conversion of nitrite to nitric oxide and thus causes a significant decrease in the residual nitrite level. Considering the relationship between the residual nitrite level and the formation of some nitrosamines, it turns out that lactic acid bacteria exert an indirect inhibitory effect by lowering the residual nitrite level. As a matter of fact, it is stated that the amount of residual nitrite is an important factor in many nitrosamines . In addite level . A rapidte level ,122,123. nitrite . Similar culture . The sam a study . Besides a study . Additio5.0–6.0) . For thiLeuconostoc carnosum, Le. mesenteroides, Lactiplantibacillus plantarum and Latilactobacillus sakei strains on NDMA and its precursors were examined using the model system during kimchi production and digestion. In addition, the ability of strains to deplete NDMA and nitrite was investigated in the study. The researchers found that the four strains directly depleted NDMA in the broth and reduced nitrite levels, with this effect being greater in L. plantarum and L. sakei. It was also reported that there is a significant reduction in the levels of NDMA and its precursors  compared to the control group in the presence of strains in kimchi production and that the reduction occurs in relation to the bacterial load. As a result, probiotic bacteria were reported to be the cause of the significant decrease in NDMA occurring in kimchi, possibly via direct degradation and inhibition of NDMA formation (37). In a study on indigenous strains  isolated from Chinese traditional fermented fish products, it was reported that three strains directly degraded NDMA and L. plantarum 120 was observed to have the highest degradation rate [In fermented sausages, lactic acid bacteria indirectly contribute to nitrosamine reduction by inhibiting decarboxylase-positive microorganisms and reducing residual nitrite levels. Approaches that use of lactic acid bacteria, which constitute the dominant microbiota in fermented sausages, can be effective in nitrosamine reduction by direct degradation and adsorption and have been frequently highlighted in recent years. One of the first studies in this regard involves a traditional fermented vegetable product called kimchi. In this study, the effects of ion rate .Lacticaseibacillus rhamnosus ŁOCK 0900, L. rhamnosus ŁOCK 0908, Lacticaseibacillus casei ŁOCK 0919, and Levilactobacillus brevis 0945) on NDMA under different culture conditions  were investigated and it was reported that the NDMA level decreased up to 50% depending on the pH, strain, NDMA concentration, incubation time, and culture conditions. It was also noted that the most effective strain in reducing the concentration and genotoxicity of NDMA was L. brevis 0945, and that these results could be related to adsorption or metabolism [Investigations on nitrosamine degradation of lactic acid bacteria strains isolated from fermented sausages carried out in fermented sausages in vitro are listed in tabolism .Lactiplantibacillus pentosus R1, Latilactobacillus curvatus R5 and L. sake L6 strains on N-nitrosamine formation and quality characteristics in Harbin dry sausage, L. curvatus showed a highly inhibitory effect on the four identified nitrosamines (N-nitrosodiethylamine (NDEA), N-nitrosodipropylamine (NDPA), N-nitrosodiphenylamine (NDPhA), and N-nitrosopiperidine (NPIP)), whereas L. pentosus R1 was only effective on NDPA and NDphA. These strains have also been reported to significantly reduce residual nitrite levels compared to the control. As a result, it was emphasized that the strains examined could be used as starter cultures to improve quality traits and reduce nitrosamine accumulation in Harbin dry fermented sausage, and among the strains examined, L. curvatus R5 gave the best performance in preventing nitrosamine formation [In a study examining the effects of ormation .L. pentosus. It was determined that L. pentosus reduced NDMA, NDEA, NPYR and total nitrosamine contents in fermented sausages by 13.8%, 1.89%, 15.55% and 11.72%, respectively, at the end of ripening. In addition, it was reported that the nitrosamine degradation rate of this strain in peptone water medium was 4.60%, 4.87% and 16.35% on days 0, 10 and 20, respectively, and the strain showed nitrite depletion ability in MRS broth. As a result, it was stated that L. pentosus can directly degrade nitrosamines in dry fermented sausages, indirectly reduce their precursors or inhibit nitrosamine formation under low pH and water activity conditions, which is associated with higher microbiological quality [In another study conducted on a Chinese dry fermented sausage type, it was reported that the nitrosamine content, residual nitrite, carbonyl content, total volatile basic nitrogen, pH and water activity were lower compared to the control at the end of ripening of sausages produced with  quality .L. pentosus R3 sourced from Chinese dried sausage. It was reported in the study that L. pentosus R3 significantly reduced the NDMA content and the levels of dimethylamine and putrescine. In the same study, it was also reported that nitrite was degraded to nitrosonium cation by acidolysis, which may promote the NDMA formation, and L. pentosus R3 directly degraded NDMA and showed antioxidant activity. Consequently, three ways were suggested for the strain to reduce NDMA; inhibition of the formation reaction, a decrease in precursors (DMA and putrescine) and direct degradation [A model system was prepared using NDMA, its precursors, and ferrous sulfate medium in a study conducted to clarify the NDMA reduction mechanism of radation .L. pentosus R3 on NDMA during production was investigated in a study on a fermented cooked sausage produced by applying fermentation (85% RH at 25°C), drying  and cooking (at 100 °C for 15 min). Sausages produced using this strain were reported to yield lower dimethylamine and carbonyl content, thiobarbituric acid reactive substances value, and content of non-haem iron values than the control group. Researchers have reported that L. pentosus R3 can directly degrade NDMA, reduce its precursors, reduce oxidation, and indirectly affect NDMA by causing a reduction in non-heme iron levels. Furthermore, they stated that low pH and water activity levels inhibit NDMA by improving the microbial quality of the sausage [Fermented sausages are generally divided into two groups, dry and semi-dry. The water activity in dry fermented sausages is below 0.90 and heat treatment is generally not applied in their production. The water activity in semi-dry fermented sausages varies between 0.90 and 0.95, and a heat treatment is usually between 60–68°C . However sausage .foods-1Fermented sausages are cured meat products that attract attention with their typical characteristic aroma. In almost all regions there are many types of products made by both traditional methods and industrial production. Fermentation, the most critical phase of these products, takes place by spontaneous lactic acid bacteria or lactic acid starter cultures. In addition, nitrate and/or nitrite is used as a curing agent in these products for product safety, characteristic cured flavor and cured color. Because of this curing agent, these products have long been in the spotlight due to the risk of nitrosamines. Various strategies have been developed to reduce nitrosamine levels due to their carcinogenic, teratogenic and mutagenic properties. In this regard, the nitrite content used was limited firstly, meanwhile, the use of reducing compounds such as ascorbic acid and sodium ascorbate have also became widespread in fermented sausages. In addition, the role of lactic acid bacteria in reducing the formation and level of nitrosamines is also being investigated. Lactic acid bacteria reduce the residual nitrite level by forming acid and thus contribute to nitrosamine reduction. Furthermore, these microorganisms inhibit the growth of biogenic amine-forming microorganisms by dominating the environment during fermentation since biogenic amines could be the precursors of nitrosamines. The nitrite depletion ability of lactic acid bacteria can also be significantly effective in lowering nitrosamine levels. In addition to all these, it is stated that lactic acid bacteria can prevent nitrosamine accumulation through direct adsorption or metabolism. However, new research is still needed to fully elucidate its mechanism.


Worsening situation of smog in Pakistan: A tale of three cities” by Ashraf et al. (2022), published in Annals of Medicine and Surgery, discussed the rapid rise in smog and air pollution in Pakistani cities including Lahore, Gujranwala, and Faisalabad, in spite of the implementation of some policy measures by the Punjab government to reduce emission. In short comment, we do not argue about the conclusion that more stringent measures are needed. However, we do take issue with the presentation of the data, in particular the interpretation of the air quality index (AQI). For example:1.According to recent data, the Air Quality Index (AQI) in certain areas of Lahore has frequently exceeded 400 μg/m3in the month of November 2021 while the safe AQI value is considered below 50 μg/m3(their reference 1); (b) According to recent IQAir reports (November 2021), air quality data of Faisalabad, Lahore and Gujranwala is 297.2 μg/m3, 271.8 μg/m3and 201.6 μg/m3respectively; and (c) Figure 1.Misinterpretation of AQI: The authors stated that (a) Recently, a short communication entitled “https://www.iqair.com/) which is based on near-surface measurements of the mass concentrations of particulate matter PM2.5  and PM10  weighted after bringing the particles in low relative humidity environment to remove water, and concentrations of four trace gases, i.e., SO2, NO2, CO, and O3. The AQI for each of these species is determined as explained in, e.g., Fan et al. [https://www.iqair.com/newsroom/what-is-aqi), IQAir mentions that “IQAir AirVisual platform AQI readings are based on the U.S. Environmental Protection Agency (EPA) National Ambient Air Quality Standards (NAAQS) to calculate AQI. Therefore, the use of the units “μg/m3” with the AQI value in the above-mentioned statements is incorrect and maybe wrongly interpreted as indicating a specific species.2.The major reason for this deteriorated air quality in winter months is smog and (b) “The colder temperatures in initial months of winters lead to smog formation which blankets the major cities of Punjab (their reference 2).Misconceptions of smog and its formation: The authors stated that (a) The AQI discussed in this paper is provided by IQAir (The cited reference (their reference 2) has not discussed winter smog, instead, the authors considered crop residue burning, higher emissions of smoke aerosols, and meteorological conditions in November as the main source of winter smog, e.g., “For years, Pakistani environmentalists have referred to November, when crop burning, higher emissions, and cold weather combine to blanket Lahore and the rest of Punjab Province with acrid smog.” Smog is a mixture of smoke and fog, which normally occurs during mid/late autumn in Pakistan. Fog is formed by tiny water droplets in the lower atmosphere and smoke is emitted from combustion processes such as in bricks kiln and steel mills, burning of garbage, growing numbers of vehicles on the road, and especially, frequent and intense crop residue burning. The combination of these two (smoke and fog) is responsible for the formation of smog over the region, in particular during favorable meteorological conditions, such as low wind speed and low boundary layers capped by a strong inversion, reducing the transport of pollutants out of the region. The mentioned cities in the published article do not face smog issues during winter due to very little burning of crop residue. High levels of smog in winter are not supported by the paper, as the authors discuss only the AQI for autumn (November) , not for winter.1), fine particulate matter (PM2.5), coarse particulate matter (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), and aerosol optical depth (AOD). This kind of research is helpful for society, the research community, and policymakers. Therefore, our commentary should be considered and published as a supplementary explanation of the discussion in this short communication.Pakistan is facing severe air quality issues throughout the year for a long time and none of the Pakistani cities meet the World Health Organization (WHO) recommended Air Quality Guidelines (AQG) and Pakistan's National Environmental Quality Standards (Pak-NEQS) . Due to Not commissioned, externally peer reviewed.There is no role of the sponsors.No patient is involved.No consent is required.Muhammad Bilal: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing—original draft Gerrit de Leeuw: Investigation, Writing—review and editing Janet E Nichol: Writing—review and editing Max P. Bleiweiss: Writing—review and editing Leiku Yang: Data curation Huabin Chua: Data curation Alaa Mhawish: Writing— review and editing Md. Arfan Ali: Data curation All authors have read and agreed to this version of the manuscript.1.Name of the registry: N/A2.Unique Identifying number or registration ID: N/A3.Hyperlink to your specific registration (must be publicly accessible and will be checked): N/AMuhammad Bilal.Nothing to disclose.


Centrocercus urophasianus), a species of conservation concern ranging across eleven western US states and into two Canadian provinces. This replicable process yielded spatial action maps, able to be prioritized by importance to maintaining range-wide genetic connectivity. We used these maps to investigate the efficacy of 3.2 million ha designated as priority areas for conservation (PACs) to encompass functional connectivity. We discovered that PACs encompassed 41.1% of cumulative functional connectivity—twice the amount of connectivity as random—and disproportionately encompassed the highest-connectivity landscapes. Comparing spatial action maps to impedances to connectivity such as cultivation and woodland expansion allows both planning for future management and tracking outcomes from past efforts.Conserving genetic connectivity is fundamental to species persistence, yet rarely is made actionable into spatial planning for imperilled species. Climate change and habitat degradation have added urgency to embrace connectivity into networks of protected areas. Our two-step process integrates a network model with a functional connectivity model, to identify population centres important to maintaining genetic connectivity then to delineate those pathways most likely to facilitate connectivity thereamong for the greater sage-grouse ( The detThe ability to quantify and visualize connectivity has improved rapidly with concomitant advances in genetic sampling and analytical approaches using non-invasive genetic approaches . ContempConnectivity mapping for conservation is most effective when developed as a two-step process: identifying population centres important to maintaining genetic connectivity, then delineating the pathways most likely to facilitate connectivity. Identifying pathways through habitat-based analyses and prioritizing by pathway benefits to populations enables decision makers to integrate connectivity into conservation designs, though this remains elusive in practice likely due to large-scale sampling requirements.Centrocercus urophasianus; hereafter, sage-grouse) is a species of conservation concern ranging across eleven western US states and two Canadian provinces. Sage-grouse populations are poised to benefit from the collection of greater than 16 000 genetic samples across their range ggplot2 [ [sf [sp ,53, Circ [sf [sp ,54, and  [sf [sp . Additio [sf [sp , PACs [5 [sf [sp , histori [sf [sp  and cont [sf [sp .. 3. 3.1Across much of the sage-grouse range, functional connectivity was relatively uninhibited  as manifested in the pairwise resistance values resulting from the circuit theory analysis thereof , though a small number of connections held exceptional importance to network-wide connectivity . Cumulative connectivity ranged widely . The largest, contiguous landscapes with the greatest concentration of connectivity were largely central to the species' range  especial. 3.2a) divided by that among PACs (figure 4b) increased steadily to a maximum observed factor of 3.5 at the 95th percentile threshold  was enveloped within PACs . The relfigure 4hreshold . A 70th a), especially those more central to the species’ range , but was occasionally peripheral where landscapes fostered connectivity among neighbouring PACs . The greatest cumulative connectivity among PACs included both pathways connecting and additions immediately adjacent to PACs (b). Thresholding cumulative connectivity to the 65th percentile resulted in continuous connectivity between PACs in the eastern  and western  halves of the species' range. At thresholds of greater than the 90th percentile, connectivity among many peripheral PACs was achieved  ensuring connectivity among all neighbouring states.Cumulative connectivity was greatest within the largest contiguous area PACs a, especi to PACs b. ThreshThe top four pairwise pathways among nodes prioritized by NCM MST edge betweenness and delineated by thresholded pairwise connectivity were located central to the species’ range and involved three high betweenness nodes . These p. 3.32; 2) exceeded the cultivation threshold, 29% (741 km2) of which was within PACs (2) exceeded woodland canopy cover thresholds (2) was within PACs  . Therefoet al.  may actuet al. ,25 charaet al.  suggestsIn cases where functional connectivity cannot be maintained or has been lost due to irreversible landscape degradation, translocation of individuals may serve to re-establish historical populations, augment failing populations and provide genetic rescue to small, imperilled populations. However, translocations should be conducted judiciously as there exist the potential risks of outbreeding depression and swamping of local adaptation ,70 as weOur model synthesis relied on a FCM developed using a k-folds cross-validation approach based on neutral genetic markers. Inference from such models can be confounded by the success of past translocation of individuals, which might result in the identification of inflated landscape connectivity. Thus, we urge careful consideration of our priority corridors among landscapes with a known history of translocations. In these cases, and in general, additional methods might be used to validate the pathways we identify. These could include the genetic identification of migrants and their offspring or the integration of direct measures of animal movement estimated from radio-marked individuals. Movement data could serve as a proxy to evaluate the efficacy of our model as applied to future conservation strategies. However, we note the majority of direct measures of animal movement do not quantify the functional (i.e. demographic) connectivity of populations. Furthermore, individual response to habitat structure will vary among species, so FCMs for other sagebrush-obligate species or those that dwell within the sagebrush ecosystem could provide insight into the generality of our priority corridors . FinallyPrioritizable and scalable pathways identified here provide a complement, rather than an overhaul, to a PAC-based conservation design. Since inception, a concern underlying PACs has been the possibility that continued degradation would render PACs isolated ‘zoos’ facing a multitude of threats to sagebrush-obligate populations . Our fin. 5Models of species distribution and abundance often guide a ‘core areas’ approach to conserving wildlife populations by targeting management and protections around key seasonal habitats. Though these strategies often wholly omit genetic connectivity in designs, or rely on assumptions about genetic connectivity from movement data and species–habitat relationships. Our novel approach gives practitioners the framework to prioritize conservation beyond seasonal habitats with confidence that their actions can help maintain pathways of connectivity between priority landscapes. Beyond sage-grouse conservation, our method for prioritizing pathways for wildlife connectivity conservation is broadly applicable across taxa, where both functional and network connectivity model types exist or can be generated from genetic data. Furthermore, combining our approach with known threats can form the foundation for comprehensive conservation planning to complement more traditional reserve designs.https://doi.org/10.5066/F7RB73V0 [https://doi.org/10.5066/F73N22PN [https://doi.org/10.5066/P9HI7OGR [Data products and metadata are publicly available as follows. (i) FCM microsatellite and spatial data: F7RB73V0 . (ii) NCF73N22PN . (iii) CP9HI7OGR . AdditioP9HI7OGR .


Few studies have genetically monitored chickens over time, and no research has been conducted on ducks. To ensure the sustainable management of key duck breeds, we used microsatellite markers to monitor Brown Tsaiya ducks over time genetically.The second, fourth, sixth to eighth generations of the Brown Tsaiya duck selected for feeding efficiency and control lines were included in this study to investigate the genetic variations, effective population size, population structure and the differentiation between populations over time with 11 microsatellite markers derived from Brown Tsaiya duck.FIS) in both lines, but no consistent increase in FIS was observed in each line. The effective population size in the second and eighth generations was 27.2 for the selected line and 23.9 for the control line. The change in allele richness showed a downward trend over time, and the selected line was slightly lower than the control line in each generation. The number of private alleles (Np) in the selected line were higher than in the control line. Moderate differentiation was observed between the second and eighth generations in the selected line (FST = 0.0510) and the control line (FST = 0.0606). Overall, differentiation tended to increase with each generation, but genetic variation and structure did not change considerably after six generations in the two lines.The results showed there were a slight decrease in the genetic variations and an increase in within-population inbreeding coefficient (This study provides a reference for poultry conservation and helps to implement cross-generation genetic monitoring and breeding plans in other duck breeds or lines to promote sustainable management. Anas Platyrhynchos), the only layer type duck breed in Taiwan, has a small body and a high egg-laying rate; their eggs are heavy and have strong shells. They are the primary source of processed eggs  in Taiwan. The feed costs account for over 80% of the total duck egg production cost. Because of continuous increases in the price of feed ingredients, to help farmers lower costs, the Livestock Research Institute in Taiwan began selecting low residual feed consumption (RFC) in 2009 [The Brown Tsaiya , in the conservation of animal genetic resources, in addition to recording basic information and appearance traits, to determine the effects of conservation and selection strategies on genetic heterozygosity, molecular markers should be also used to investigate the genetic structure [Microsatellite markers have been widely used in studies on indigenous and commercial duck population conservation in India, the Philippines, Vietnam, China, and other countries –7 becausFIS) and more markers deviating from Hardy–Weinberg equilibrium. Since the RFC selected line is still under selection, to ensure sustainable management, the aim of this study is to integrate our previous study and conduct genotyping in subsequent generations of the RFC selected and control line to evaluate the effects of continuous selection and breeding strategies on the genetic variation and differentiation over time.In our previous study, we used 11 Tsaiya microsatellite markers to investigate the genetic structure of various Brown Tsaiya duck lines, including the second and fourth generations of the RFC selected and control lines. Compared with the germplasm-preserved Brown Tsaiya duck (without selection), there was almost no change in genetic variations between the population separated by two generations, while RFC control line showed a decrease in the number of allele and heterozygosity . Lai et The animals, management methods, and experimental protocols used in this study were approved by the Institutional Animal Care and Use Committee of the Ilan Branch of the Livestock Research Institute, Council of Agriculture, Executive Yuan, Taiwan .The experimental animals were from 10 populations of the second, fourth, sixth, seventh, and eighth generations of the selected and control lines. The two lines’ genotypes of the second and fourth generations were obtained from the previous study  , and theFor each duck in this study, 2 to 3 mL of blood were drawn from the superficial plantar metatarsal vein or wing vein. The genomic DNA of the ducks was extracted from the blood samples by removing plasma with a Gentra Puregene Blood Kit  under the instructions; we followed Bush et al  to adjus2), 0.2 μM deoxyribose nucleotide triphosphate (dNTP), 0.2 μM forward and reverse primers with fluorescent-labeled in the forward primer, and 50 ng of genomic DNA. The PCR cycling program was as follows: 94°C for 10 min, 30 cycles at 94°C for 20 s, 60°C for 30 s, 72°C for 30 s, and final elongation at 72°C for 10 min. The PCR products were analyzed through gel electrophoresis in 1% agarose gels, visualized using ethidium bromide staining, and pooled based on fragment size and fluorescent color for subsequent capillary electrophoresis analysis. The amplified microsatellite PCR products were denatured using Hi-Di formamide and analyzed using a DNA analyzer . Fragment size was estimated using GeneScan 500 LIZ Size Standard . The resulting fragment analysis data and size of the alleles were analyzed using Peak Scanner Software version 1.0 .The microsatellite markers were screened from Brown Tsaiya ducks . After ta), observed (HO), and expected (HE) heterozygosity [e), and estimate Wright’s F-statistics for each locus, namely within-population inbreeding coefficient (FIS), among-population genetic differentiation (FST), and population inbreeding coefficient (FIT), and to perform the Hardy–Weinberg equilibrium test [e) was estimated using the Jordan–Ryman temporal method and plan I in NeEstimator (V2) [FST between populations as described in Weir and Cockerham [p) were performed using GenAlEx (v6.503) [The genetic variation data, which consist of the number of alleles   with contor (V2) . FSTAT (tor (V2)  was usedockerham  to evalu(v6.503)  to dividIn the clustering analysis, the adegenet R package performed principal coordinate analysis (PCA) and plotting . The cluF-statistics of the 11 Tsaiya duck microsatellite markers in the selected and control lines. Fifty-four alleles were observed, and all 11 loci were polymorphic. The number of alleles (Na) ranged from 2 to 8, with an average of 4.9 alleles per locus. The average number of effective alleles (Ne) per locus was 2.900 ranged from 1.911 (APT033) to 4.106 (APT004). The observed heterozygosity (HO) among 11 microsatellite loci had a range from 0.227 (APT033) to 0.758 (APT026), with the average of 0.531. The expected heterozygosity (HE) ranged from 0.477 (APT033) to 0.757 (APT004), with an average of 0.627. The PIC ranged from 0.363 (APT033) to 0.720 (APT026), with an average of 0.563. Among the 11 microsatellite markers, seven markers were highly polymorphic (PIC>0.5), and four markers were moderately polymorphic (0.5>PIC>0.25). Nevertheless, the Ewens-Watterson test indicates APT008 and APT026 are not selectively neutral  to 0.502 (APT033), with an average of 0.102. The FIT ranged from −0.064 (APT026) to 0.538 (APT033), with an average of 0.154. The FST ranged from 0.021 (APT032) to 0.133 (APT010), with an average of 0.059. The results indicated that 5.9% of the overall genetic variation was due to differences between populations, whereas differences among individuals within each population caused 94.1% of total genetic variation. neutral . In addia was higher in most of the generations of the selected line than in the control line; only S2 and S8 had slightly lower Na values than did C2 and C8. Ne, HO, HE, and PIC in the control line were higher than those in the selected line, except for the eighth generation. The mean AR values estimated based on the minimum sample size 17 ranged from 3.189 (S8) to 3.727 in selected line, while 3.545 (C8) to 3.777 (C6) in control line. The selected line is slightly lower than the control line in each generation, especially in the eighth generation. The number of private alleles (Np) ranged from 0.000 (S2) to 0.364 (S7) in selected line, and 0.000  to 0.091 (C2). Compared to the selected line, there was almost no private allele in the control line. However, except for Np no significant difference in genetic variation was observed between the lines (p>0.05).The inter-line comparison showed that NFIS was positive in all generations of both lines, but no difference between the lines was observed.Some markers deviated from the Hardy–Weinberg equilibrium in the sixth to eighth generations, namely APT001 and APT033 in the sixth generation of both lines, APT001 in S7, APT008 and APT033 in S8, and APT001 and APT008 in C8. a, Ne, HO, HE, and PIC slightly increased then decreased with each generation, while those continued decreasing slight in the control line. The change in AR showed a downward trend over time. FIS ranged from 0.082 (S2) to 0.137 (S7) in the selected line and from 0.048 (C2) to 0.165 (C4) in the control line, and no consistent increase was observed in each line. In addition, no significant differences in genetic variation were observed between generations in each line (p>0.05).The intra–line comparison showed that the selected line, NThe effective population size (Ne) in the second and eighth generations, estimated through the Jorde–Ryman temporal method, was 27.2 for the selected line  and 23.9 for the control line ; Ne was lower in the control line than in the selected line. We also estimated Ne in two generations of each line; the closer the two generations were, the higher the Ne was. For example, the upper limits of the confidence intervals in the seventh and eighth generations of the two lines were infinity .The result of FreeNA  Supplem showed tFST between generations of the selected line and its control line. The intra-line comparison revealed low FST values in the second and sixth generations: 0.0307 and 0.0217, respectively. Moderate FST values were observed in the fourth, seventh, and eighth generations: 0.0540, 0.1123, and 0.1271, respectively. FST gradually increased from the second to fourth generations, decreased in the sixth generation, and increased again to 0.1123 in the seventh generation and to 0.1271 in the eighth generation. Overall, differentiation tended to increase with each generation.FST values range from 0.0074 to 0.0510. However, only moderate differentiation was observed between S2 and S8 (FST = 0.051). Significant differentiation was observed between C2 and C7 to C8 and between C8 and C4 to C6, with FST values ranging from 0.0240 to 0.0606. Only moderate differentiation was observed between C2 and C8 (FST = 0.0606). The results indicate that FST increased as the generation gap widened for both the selected and control lines.The intra-line comparison in the selected line showed that S8 was significantly differentiated from S2, S4, and S6, and the The AMOVA results in Population PCA was performed using the adegenet R package . The perFST and AMOVA results.e of Korean and Bangladeshi ducks is 2.8 to 3.7 [e of each generation of the two lines was 2.4 to 3.0, which is not significantly different from those observed in other studies.So far, FAO has not offered recommended microsatellite markers for ducks, so this study used the 11 microsatellite markers from Brown Tsaiya ducks  with sup8 to 3.7 , and tha8 to 3.7 . In thisa per locus was 7.3, and the mean Ne per locus was 3.6. The mean HO was 0.474, the mean HE was 0.690, and the mean PIC was 0.646. All markers were highly polymorphic, except for APT001 and APT032, which were moderately polymorphic [a was 11.3 per locus, the mean Ne was 5.4, the mean HO was 0.591, the mean HE was 0.747, and the mean PIC was 0.708 [To confirm the polymorphism of the markers used in this study, we also tested the 11 microsatellite markers in Pekin duck, Kaiya, and several lines of Brown and White Tsaiya ducks to investigate polymorphisms in other breeds. The mean Nymorphic . Compareas 0.708 ; the genThrough the Ewens-Watterson test, we found that APT008 and APT026 were non-neutral markers. However, Pampoulie et al  pointed A. platyrhynchos) genome database (GCF_015476345.1_ZJU1.0) through BLAST to find possible chromosomal locations. The 11 markers were distributed on chromosomes 1, 2, 3, 7, and Z  as an example, it is necessary to increase the number of markers by 2 to 11 times to achieve the same resolution of microsatellite markers [However, in five microsatellite markers, the number of alleles identified is equal or less than four. The low N markers . Therefoa, and the allele frequencies and HE estimated by samples may be quite different from the real population. However, the sample size of 25 to 30 is representative, and it is little benefit of further increasing the sample size per population. Since the sample size in the second and fourth generations of this study is less than 30, the genetic variation may be underestimated [The results showed there were slightly decrease in the genetic variations, especially about the heterozygosity in the control line. Among them, the genetic variations of the second and fourth generations are slightly lower than those of the sixth generation. Hale et al  pointed stimated . For subFIS in the both line, although no consistent increase in FIS was observed in each line. It indicated there were heterozygosity deficits in both the selected and control lines. Studies have indicated that possible causes of heterozygosity deficits include selection, inbreeding, geographic isolation, sampling error, the Wahlund effect, and null alleles [And there was also increase in  alleles .FIS of each population was similar to the one of the total population  method, which is not strongly affected by genetic drift, resulting in higher Ne values. The LD method is limited by random mating and lifetime monogamy , which aFIS each generation may have been caused by selection for RFC, genetic drift, and null alleles. Also, RFC selection may result in the decline in AR. However, the consistent FIS over time, Ne, and the performance monitoring results indicate no severe inbreeding depression. The follow-up genetic monitoring should be performed.In summary, the heterozygosity deficit and change in FST lower than 0.05 indicates nearly no differentiation, 0.05 to 0.15 indicates moderate differentiation, 0.15 to 0.25 indicates high differentiation, and values higher than 0.25 indicate extremely highly differentiation. Except for the sixth generation, the second through eighth generations was increasingly differentiated between the two lines  in this study were 0.1123 and 0.1271, respectively. Similar to the genetic analysis of Taiwan’s duck breeds and lines [FST between Brown Tsaiya duck lines  separated by more than ten generations was 0.092 to 0.167. The result indicated that the differentiation between the selected and control lines has reached the level of different lines. And the pairwise FST between lines from 0.0307 (C2 and S2) increased to 0.1271 (C8 and S8), the result is similar to Hungarian study. The pairwise FST between breeds ranged from 0.15 to 0.28 in 2002 and slightly increased to 0.21 to 0.30 after 15 years, the differentiation increased, and genetic similarity between breeds decreased over time [The pairwise nd lines  indicateFIT (0.154) was mainly affected by FIS (0.102) rather than by FST (n by FST . The AMOn by FST  indicateAs for PCA , the firFST results. When K was 2, the two lines formed independent clusters by the seventh generation. However, the proportions of inferred clusters on the left one-third of the samples in C6 were highly similar to the S6, and those in the other two-thirds of the samples were similar to C4. This may have been caused by the temporary introduced the selected line to the control line. Overall, the differentiation between the selected and control lines increased with each generation.The STRUCTURE results are consistent with the pairwise FIS did not increase considerably, indicating that the breeding and population management strategies were effective. To preserve genetic heterozygosity, rotational mating schemes, or increasing the number of drake families under the same population can be used if necessary. The results of this study indicate that genetic variation and structure did not change considerably after six generations with the current breeding and mating strategy and can be used as a reference for other poultry conservation research. Genetic monitoring should be performed regularly to conserve the germplasm, but the intervals between analyses can be longer to reduce costs.With the strengthening effects of climate change on the livestock industry, promoting “Better Feed Efficiency Brown Tsaiya” can help farmers reduce feed costs by 10% and mitigate the negative effects of extreme weather. However, maintaining large breeding populations is difficult with a limited workforce and management costs. Smaller poultry populations also often result in changes in allele frequency. Therefore, changes in heterozygosity over time must be monitored. Few studies have genetically monitored chickens over time, and no such study has been conducted on ducks. To ensure the sustainable management of key duck breeds, we used microsatellite markers to monitor ducks over time genetically. The results indicate that the markers reflect changes in heterozygosity and differentiation between the selected line and its control line. Although selection, genetic drift, and null alleles may have slightly decreased the heterozygosity and may result in the loss of allele in the two lines, heterozygosity remained, and