Perspective traces the evolution of certain central notions in the theory of Generative Grammar (GG). The founding documents of the field suggested a relation between the grammar, construed as recursively enumerating an infinite set of sentences, and the idealized native speaker that was essentially equivalent to the relation between a formal language (a set of well-formed formulas) and an automaton that recognizes strings as belonging to the language or not. But this early view was later abandoned, when the focus of the field shifted to the grammar's strong generative capacity as recursive generation of hierarchically structured objects as opposed to strings. The grammar is now no longer seen as specifying a set of well-formed expressions and in fact necessarily constructs expressions of any degree of intuitive “acceptability.” The field of GG, however, has not sufficiently acknowledged the significance of this shift in perspective, as evidenced by the fact that  observations about string acceptability continue to be treated as bona fide data and generalizations for the theory of GG. The focus on strong generative capacity, it is argued, requires a new discussion of what constitutes valid empirical evidence for GG beyond observations pertaining to weak generation.This  While linguists agree on this focus, they nevertheless tend to uncritically assume that judgments of the acceptability of strings constitute data for GG. But this assumption is baseless, and a renewed discussion of GG's empirical basis is in order.There exists a contradiction between the near-universal acceptance of acceptability judgments as a source of data for Generative Grammar (GG) on the one hand and the theory's express focus on LSLT) defined as the “primary concern” of syntactic theory “to determine the grammatical sentences of any given language […]” (57). Chomsky (SS) elaborates:Chomsky , LSLT de Chomsky , SS elabL is to separate the grammatical sequences which are sentences of L from the ungrammatical sequences which are not sentences of L […]. The grammar of L will thus be a device that generates all of the grammatical sequences of L and none of the ungrammatical ones.” .“The fundamental aim in the linguistic analysis of a language LSLT, 95); hence, “the sequences generated by the grammar as grammatical sentences must be acceptable, in some sense, to the native speaker […]” . The adequacy of a grammar can be assessed by “[determining] whether or not the sequences that it generates are actually grammatical, i.e., acceptable to a native speaker” . Consequently, “the linguist's task [is] that of producing […] a grammar [that generates] all and only the sentences of a language […]” .The set of sequences so determined “corresponds to the ‘intuitive sense of grammaticalness’ of the native speaker” (Early View (EV), the idealized native speaker is the human equivalent of an automaton in the theory of formal languages, which accepts (recognizes) or rejects a given string depending on whether or not it is part of the set of legal sequences. While the importance of hierarchical structures underlying the sequences was recognized to be of central importance, the formal systems used at the time—Post-style rewrite rules plus transformational rules—ultimately enumerated strings .Later works of Chomsky's are explicit in rejecting the EV and its view of the idealized native speaker as a human automaton. Perhaps the first clear articulation of this shift appears in Chomsky , where wlanguage as a set of sentences is a corollary of the shift of the focus of attention from sentences to structures:This dismissal of the view of a “For each sentence, the grammar determines aspects of its phonetic form, its meaning and perhaps more. […] [It] is said to ‘weakly generate’ the sentences of the language and to ‘strongly generate’ the structural descriptions of these sentences” Chomsky, , p. 220.strongly generates structural descriptions (SDs), not strings; the latter can at best be said to be generated in some weak sense, in that the “phonetic form” associated by the grammar with any SD has sequential properties  in fact “[A] GG will not generate the set of sentences that a speaker-hearer will regard as acceptable; indeed, it is virtually a criterion of adequacy that it should not, since so many different factors enter into such judgments”  one way or another”  cannot be interpreted in this way.Chomsky ((I know) [who [John [kissed _]]]x is such that John kissed x”)(“which person (I know) [who [John [kissed Mary]]]wh-operator has no variable to bind, and consequently cannot be assigned an interpretation. Importantly, we cannot simply “neglect” the fronted wh-phrase and interpret (2) as meaning (I know) John kissed Mary, a fact that Chomsky attributes to the principle of Full Interpretation—an interface condition, in current parlance. Does this mean that we want to block generation of (2), while allowing generation of (1)? Chomsky explicitly denies this, arguing that such a move would redundantly replicate the effect of Full Interpretation. Consequently, both SDs in (1) and (2) are grammatical (generated by the grammar); the “deviance” of (2) is due to an extraneous principle of interpretation. But the fact that the string deriving from (2) is “deviant” per se is of no immediate concern to the theory of grammar.In (2), the LSLT (145), the goal of the theory is not to construct a grammar that generates a set of well-formed formulas including Colorless green ideas sleep furiously but excluding Furiously sleep ideas green colorless, but to explain why the SD assigned to the latter cannot be mapped onto an analogous interpretation. The naturalness of the typographical or acoustic object is of no immediate relevance to the theorist , the empirical success of GG depends on its ability to correctly model the speaker's knowledge of sound-meaning relations, not the intuitive acceptability of strings:On this “Linguistic expressions may be ‘deviant’ along all sorts of incommensurable dimensions, and we have no notion of ‘well-formed sentence’ […]. Expressions have the interpretations assigned to them by the performance systems in which the language is embedded: period” Chomsky, , p. 27.In later works, Chomsky entertains the idea that generation of SDs proceeds freely via the operation Merge, with constraints imposed only by external systems. For instance, Chomsky , p. 111 “Merge can apply freely, yielding expressions interpreted at the interface in many different kinds of ways. They are sometimes called ‘deviant,’ but that is only an informal notion. […] The only empirical requirement is that [the interfacing systems] assign the interpretations that the expression actually has, including many varieties of ‘deviance”’ Chomsky, , p. 144.Chomsky , p. 3f. On this RV, there exists no notion of well-formedness that is given independently of whatever is strongly generated by the I-language. The grammar does not specify a set of legal strings but an infinity of SDs; the only empirical success criterion is that the SDs postulated by the theorist have the properties in interpretation and externalization they do.While the field ostensibly embraced the focus on SGC and SDs championed by Chomsky, the EV remains widely adopted in actual practice. Grammaticality and acceptability are standardly equated, and I-languages taken to determine sets of well-formed strings/sentences. The following quotes, randomly culled from popular textbooks, are representative:grammatical if native speakers judge it to be a possible sentence of their language” , marginally well-formed, or ill-formed ” Carnie, , p. 14.“[A] sequence of words is called a string. Putting a star at the start of a string is a claim that it isn't a grammatical sentence of the language in question” Adger, , p. 4.sic] is to obtain a form of information that scarcely exists within normal language use at all—namely, negative information, in the form of strings that are not part of the language”  adherence to the EV, acceptability judgments continue to take center stage in GG, and a good deal of the literature on experimental syntax has been devoted to refining their elicitation Sprouse, . Sprousemodulo performance-related factors). This view is most explicitly espoused by Frampton and Gutmann , ignoring the fact that this notion has no obvious relevance on the RV. A direct outgrowth of this ideology is the extensive reliance on highly stipulative features as licensors of structure-building Chomsky, , p. 6, lHeilikes Johni is “unacceptable,” or that it lacks the intended reading; we can say that (2) above is “deviant,” with an implicit understanding that we're referring to the absence of an interpretation analogous to (1). This innocent informal usage aside, however, the “(un)acceptable” status of sentences remains the de-facto empirical benchmark for theoretical proposals within GG, and informal observations about weak generative capacity, clad in technical terms, are standardly elevated to the status of generalizations to be accounted for (cf. the case of islands mentioned above). The field must overcome these limitations and move on to a theoretical characterization of possible SDs  and their interface properties . Despite this shift, the field has retained a methodological obsession with the intuitive well-formedness of strings and associated notions such as “overgeneration” (E-language).Chomsky , p. 63 nThe author confirms being the sole contributor of this work and approved it for publication.The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Rothia and Haemophilus compared to the HC group, and significantly decreased Haemophilus and increased Oribacterium compared to the UC group. By combining the genera selected by the random forest algorithm in machine learning, followed by confirmation with 10-fold cross-validation, we were able to distinguish the PSC group from the HC group with the area under the curve (AUC) of 0.7423, and from the UC group with the AUC of 0.8756. Our results indicate the potential of salivary microbiota as biomarkers for a noninvasive diagnosis of PSC.Primary sclerosing cholangitis (PSC) is a liver disease known for its frequent concurrence with inflammatory bowel disease. Dysbiosis of the gut microbiota in PSC was reported in several studies, but the microbiological features of the salivary microbiota in PSC have not been established. Here we compared the salivary microbial communities of 24 pediatric-onset PSC patients, 16 age-matched ulcerative colitis (UC) patients, and 24 healthy controls (HCs) by analyzing the bacterial 16S rRNA gene sequence data. The species-richness (α-diversity) showed no significant between-group differences, whereas the overall salivary microbiota structure (β-diversity) showed significant differences among the three groups. Taxonomic assignment revealed that the PSC salivary microbiota were characterized by significant decreases in the abundance of  PSC is also known for its high association with inflammatory bowel disease (IBD), mainly ulcerative colitis (UC), with a prevalence of 70–80% in adults1, and with the same proportion or an even higher proportion in children4. Conversely, as many as 8.1% of IBD patients develop PSC5. It was also reported that PSC-like bile duct lesions occur frequently even with normal biochemical profiles in children with IBD6.Primary sclerosing cholangitis (PSC) is a liver disease characterized by multiple stenoses due to chronic inflammation and fibrosis in the intrahepatic and extrahepatic biliary system. The disease eventually progresses to end-stage liver disease, resulting in poor prognoses7. However, ERCP is associated with complications such as pancreatitis. To avoid complications, magnetic resonance cholangiopancreatography (MRCP) has been proposed as an alternative method for the diagnosis of PSC, but its sensitivity is approximately 81–86% in children, with a lower resolution in younger patients and the need for sedation in some cases9. Thus, additional noninvasive diagnostic biomarkers are desirable for the evaluation of the presence of PSC.In light of this frequent concurrence of PSC and IBD, the diagnosis of either of these diseases should consider the concurrence of the other disease. Cholangiography is mandatory for the diagnosis of PSC, and endoscopic retrograde cholangiopancreatography (ERCP) has been used for the diagnosis of PSC in adults and children14, implying that gastrointestinal inflammation and indigenous microbes are associated with the pathogenesis and prognosis of PSC, and that early intervention may also produce better prognoses. The gut microbiota of adult PSC patients were recently intensively evaluated by using 16S rRNA gene sequences23. Those studies indicated the enrichment of particular bacterial genera including Veillonella23, Enterococcus23, Lactobacillus20, Ruminococcus22, Streptococcus23, Rothia23, and Fusobacterium22 in the feces of PSC patients. We also reported the enrichment of several species, some belonging to these genera, in a Japanese pediatric-onset PSC cohort2.In pediatric and adult PSC patients, the oral administration of antibiotics was reported to decrease the serum levels of alanine aminotransferase (ALT) and γ-glutamyltranspeptidase (GGT), with histological improvement24, several studies have described alterations of salivary microbiota in patients with various diseases. These include cirrhosis25, IBD27, pancreatic cancer29, lung cancer30, colorectal cancer31, IgA nephropathy32, celiac disease33, Behcet’s disease34, and rheumatoid arthritis35. The involvement of salivary microbes in these diseases is unclear, but a correlation between the gut and oral microbiota was suggested36. In addition, changes in the salivary microbiota in systemic diseases may be a resource of microbial biomarkers specific to the diseases, which could contribute to the development of simple and noninvasive diagnoses based on microbial profiling with saliva samples.In addition to close associations between dysbiosis of the gut microbiota and diseasesTo date, there has been no report on the salivary microbiota of PSC patients. As the initial step in the exploration of potential biomarkers for the noninvasive diagnosis of PSC, we performed a bacterial 16S rRNA gene sequence analysis to characterize the salivary microbiota of pediatric-onset PSC patients in a comparison of their microbiota with those of pediatric-onset UC patients and healthy controls (HCs).We recruited 24 PSC and 16 UC patients without PSC whose age of onset was <18 years from Saiseikai Yokohamashi Tobu Hospital  between May 2013 and October 2015, and healthy volunteers without any symptoms  also confirmed no significant difference between the PSC samples with and without SASP treatment, or between the PSC patients treated and untreated with ursodeoxycholic acid (UDCA), mesalazine, and probiotics respectively  plot based on the weighted UniFrac distance metric showed that many of the PSC and UC samples segregated from the HC samples, suggesting that the salivary microbiota structure of both the PSC and UC groups differed from that of the HC group Fig. . The PERStreptococcaceae, Pasteurellaceae, and Lachnospiraceae showed significant differences among the three groups. Of these three families, a lower Pasteurellaceae abundance and a higher Lachnospiraceae abundance were observed in the PSC group compared to both the UC and HC groups . Moreover, the abundance of Haemophilus was also significantly lower in the PSC group than that in the UC group (p = 0.0007). Conversely, the abundance of Oribacterium was significantly higher in the PSC group compared to the UC group (p = 0.0036). Additionally, the abundance of Streptococcus was significantly lower in the UC group compared to the HC group (p = 0.0159).The taxonomic assignment at the genus level identified a total of 114 bacterial genera, of which we further evaluated the major 16 genera with the relative mean abundances of >0.5%, accounting for 92.2% of the total abundance  curves were based on the out-of-bag (OOB) error rates in the RF models. We used the area under the curve (AUC) of these ROC curves to find the combination of multiple taxa contributing most to the discrimination of the three groups from the 29 abundant genera with relative mean abundances of >0.1%. The best model was selected according to the best OOB-AUC, which was observed for eight and six genera between the PSC and HC groups, and the PSC and UC groups, respectively  models using the AUC-RF packageely Fig. .Figure 3Haemophilus, Streptococcus, Aggregatibacter and Oribacterium) were the common contributors to distinguish the PSC from both the HC and UC groups  contributed to distinguishing the PSC from the HC group  using the RF-selected genera more clearly distinguished the PSC from the HC and UC groups than the PCA using the 29 genera with the mean abundance >0.1%  were the species distinguishing the PSC group from the HC group  were the species distinguishing the PSC group from the UC group  were markedly enriched in the present pediatric-onset PSC group compared to the UC and healthy control groups, and were shown to be the species contributing to the discrimination of the two groups. Similar to the pediatric-onset PSC patients analyzed here, the family Lachnospiraceae was increased in the salivary microbiota of children with celiac disease33. On the other hand, Streptococcus sanguinis was concurrently enriched in celiac disease patients33, whereas this species was significantly decreased in our PSC group  and then transported on ice to the laboratory within 24 hr. At the laboratory, the saliva samples were suspended in 20% glycerol and phosphate-buffered saline (PBS), and then immediately frozen in liquid nitrogen and stored at −80 °C until further analysis26. The 16S rRNA gene V1–V2 region was amplified by polymerase chain reaction (PCR) using the forward primer 27Fmod (5′-CCATCTCATCCCTGCGTGTCTCCGACTCAGNNNNNNNNNNagrgtttgatymtggctcag-3′), containing the 454 primer A and a unique 10-bp barcode sequence for each sample (indicated by Ns), and the reverse primer 338 R (5′-CCTATCCCCTGTGTGCCTTGGCAGTCTCAGtgctgcctcccgtaggagt-3′) containing the 454 primer B38. The PCR was performed using 50 μL of 1× Ex Taq PCR buffer composed of 10 mM Tris-HCl (pH 8.3), 50 mM KCl, and 1.5 mM MgCl2 in the presence of 250 μM dNTPs, 1 U Ex Taq polymerase , forward and reverse primers (0.2 μM), and approximately 20 ng of template DNA.The isolation of bacterial DNA from the salivary samples was performed as describedThermal cycling was performed in a 9700 PCR System  with the following cycling conditions: initial denaturation at 96 °C for 2 min, followed by 25 cycles of denaturation at 96 °C for 30 sec, annealing at 55 °C for 45 sec, and extension at 72 °C for 1 min; and final extension at 72 °C. PCR amplicons were purified using AMPure XP magnetic purification beads  and quantified using the Quant-iT PicoGreen dsDNA Assay Kit (Life Technologies Japan). An equal amount of each PCR amplicon was mixed and subjected to sequencing with the 454 GS FLX Titanium platform  according to the manufacturer’s instructions.38. Briefly, after multiplexed sequencing of the 16S amplicons, sequences were assigned to samples on the basis of their barcode sequences. Reads with an average quality value <25, inexact matches to both universal primers, and possible chimeric reads, totally accounting for 43–44% of all reads, were removed  and NCBI genome databases using the GLSEARCH program. For assignment at the phylum, family, genus, and species levels, the sequence similarity thresholds of 70%, 90%, 94% and 96% were respectively applied. All of the high-quality 16S V1–V2 sequences analyzed in this study were deposited into the DDBJ/GenBank/EMBL database (accession no. DRA005698).We then sorted the selected reads with the average quality value and grouped them into OTUs by clustering using the UCLUST algorithm with a 96% identity threshold50. We performed a principal coordinate analysis (PCoA) to visualize the similarities or dissimilarities in the microbiome structure in the UniFrac analysis. We conducted a PERMANOVA to compare the overall microbiome structure, and the p-values were adjusted for multiple testing by the Benjamin-Hochberg procedure. We used the observed and Chao 1-estimated OTU numbers and Shannon’s index to evaluate the richness and diversity of the overall microbial community. The similarity of the relative abundance at the phylum, family, genus, and species levels was assessed using the Kruskal-Wallis test followed by the Steel-Dwass test for multiple comparisons.Comparisons of the categorical variables were done using the Chi-squared test, Fisher’s exact test, Mann-Whitney U-test, and Kruskal-Wallis test where appropriate. The UniFrac distance was used for the assessment of the dissimilarity (distance) between any pair of samples41 package. All receiver operating characteristic (ROC) curves presented for RF models were based on the out-of-bag (OOB) error rates. The area under the curve (AUC) of these ROC curves was used to find the most discriminatory variables (genera or species). The first RF was build, using all the variables, which provides the initial ranking of the variables according to its importance according to the mean decrease Gini. In the subsequent steps, 5% of the less important variables according to the initial ranking were eliminated. The RF was built with the remaining variables, and the AUC based on OOB predictions (OOB-AUC) of the RF was computed in each model. The best model was selected with the best OOB-AUC value. The best RF model was further confirmed by evaluating the mean AUC of a 10-fold cross-validation repeated 20 times using the AUC-RF41 package. All of these analyses were performed using the R software program (v3.3.1). All methods were carried out in accordance with relevant guidelines and regulations.Random forest (RF) models were generated using the AUC-RFSupplementary Files


Vascular endothelial growth factors (VEGFs) and their receptors play crucial roles in the formation of blood and lymphatic vessels during embryogenesis, and also under pathologic conditions in the adult. Despite intensive efforts over the last decades to elucidate the precise functions of VEGFs, transcriptional responses to VEGF receptor stimulation are still not fully characterized. To investigate the specific transcriptional effects of VEGFR-2 and VEGFR-3 activation, we performed a correlation analysis of previously published CAGE sequencing and microarray data of human lymphatic endothelial cells (LECs) stimulated with distinct VEGFs acting through either VEGFR-2 or VEGFR-3. We identified that specific activation of VEGFR-3 by VEGF-C156S results in the downregulation of many genes involved in immune regulation and inflammation, suggesting that VEGFR-3 stimulation has direct anti-inflammatory effects. Comparing CAGE and microarray data sets, we furthermore identified a small number of genes that showed a receptor-dependent response in LECs, demonstrating that these receptors, despite activating very similar signaling pathways, fulfill overlapping but not identical functions within the same cell type (LECs). VEGFs exert their function by binding to the three known VEGFRs, VEGFR-1, VEGFR-2 or VEGFR-3, which are expressed by blood vessel endothelial cells (BECs) in case of VEGFR-1 and -2, and lymphatic vessel endothelial cells (LECs) in case of VEGFR-2 and -3. Some expression of VEGFR-3 in angiogenic blood vessels has been described as well2. In addition, VEGFs bind to co-receptors such as neuropilins (NRP) 1 and 2 as well as heparan sulfate proteoglycans, that do not signal directly but modulate the interaction between VEGFs and VEGFRs and thereby affect VEGF signaling indirectly1.The vascular system, consisting of blood and lymphatic vessels, is crucially dependent on vascular endothelial growth factors (VEGFs) and their receptors (VEGFRs), which regulate the proliferation and function of endothelial cells. In humans, the VEGF family comprises five ligands, placenta growth factor (PLGF), VEGF-A, VEGF-B, VEGF-C and VEGF-D, that are structurally related and predominantly present as homodimers in their mature form3. Of note, a mutated form of VEGF-C, in which Cys156 is replaced by a Ser residue (VEGF-C156S), displays reduced affinity for VEGFR-2, and has thus been regarded as a selective VEGFR-3 stimulator4.The individual members of the VEGF family display selective binding affinities for one or several VEGFRs. PLGF and VEGF-B exclusively interact with VEGFR-1. VEGF-A, the most potent inducer of endothelial responses within the family, binds to both VEGFR-1 and VEGFR-2. Although the affinity of VEGF-A is higher for VEGFR-1 than for VEGFR-2, the latter receptor has a much higher kinase activity and is thus regarded as the most important receptor for transmitting the effects of VEGF-A. VEGF-C and VEGF-D differ from the other ligands of the family in that they are produced as immature precursor proteins, requiring proteolytic maturation in order to gain their full activity, and preferentially bind to VEGFR-3. In their fully mature form, however, both ligands also act as VEGFR-2 agonists5. This in turn leads to the phosphorylation of specific Tyr residues in the cytoplasmic tail of the receptor, which serve as docking sites for adapter proteins needed to initiate multiple downstream signaling cascades such as the PI3K-AKT, PLC-γ and Ras-Raf-ERK signaling pathways. The biochemical processes immediately downstream of receptor activation have been investigated to considerable detail  and identified several TFs involved in this response. The majority of these TFs are well known ‘immediate early’ TFs that are induced upon signaling through various receptor tyrosine kinases such as EGR, FOS and JUN. Importantly, we also identified TFs with LEC-specific functions during VEGFR-3 signaling. For example, the homeobox TF HOXD10 that is constitutively present in LECs but not in BECs, is required for the induction of a second, downstream TF, namely NR4A1 . We identified multiple downregulated genes that were frequently associated with pro-inflammatory functions. Furthermore, we performed a combined analysis of the CAGE sequencing data and our previously published microarray-based gene expression data of primary human LECs treated with VEGF-A or fully mature VEGF-C, resulting in activation of either VEGFR-2 or of both VEGFR-2 and VEGFR-3, respectively10. We found that even though the majority of target genes are comparably regulated by VEGFR-2 and VEGFR-3 activation in human LECs, a small number of distinct genes showed receptor-specific responses within the same cell type.Our previous analysis of the CAGE RNA sequencing data only revealed upregulated but not downregulated genes after VEGF-C156S treatment of LECsn to the preceding time point tn-1 using the EdgeR method11. Since this analysis likely failed to identify genes with small, gradual changes in gene expression, we re-analyzed the data set comparing each time point tn to the baseline time point t0 using paired DESeq2 >0.6) and 1012 downregulated  peaks  to 480 min ref.  Fig. 1aFig. 1a. eq2 ref. . Among 86) peaks . Activat6) peaks .9. Among the 158 overlapping genes, we found several important lymphatic TFs such us KLF4, SOX18, and MAFB  CAGE peaks corresponded to 501 upregulated and 772 downregulated genes, according to the current CAGE peak annotation . Furtherand MAFB . Interes9, the upregulated genes were enriched for GO terms related to chromatin organization, mRNA expression, and protein translation and localization , middle phase genes (150 to 240 min) and late phase genes (300 to 480 min) . Then, wlization . We founlization . Similar10, 60 min, 240 min, 480 min and 24 h after stimulation. We decided to use the VEGF-A data to identify genes regulated by either VEGFR-2 or VEGFR-3 stimulation, comparing them to the VEGF-C156S stimulation time course at the three overlapping time points 60 min, 240 min, and 480 min , and that showed at least a 4-fold difference in their log2FC induced by VEGF-A and VEGF-C156S. We identified 108 differentially regulated (DR) genes at the 60 min time point, 232 at the 240 min time point, and 194 at the 480 min time point , wildtype VEGF-C (500 ngml−1) and VEGF-C156S (1.5 μgml−1) incubation at 60, 240 and 480 min, using qPCR. Consistent with our in silico results, RCAN1 was selectively induced at the 60 min time point  are lower26. This suggests that the increased number of DE genes identified here is not simply due to false positives. Secondly, we used a different scheme to calculate the contrasts, comparing each time point tn of the stimulation with the baseline t0 (0 min), whereas previously, tn was compared to tn-1, which probably resulted in type II errors  in case of genes with small and/or gradual changes in expression. Finally, using a multi-factorial design, we now adjusted for differences between the 3 individual LEC donors, which conceivably increased the statistical power of our analysis.Activation of VEGFR-3 results in various cellular responses in lymphatic endothelial cells, including cell migration, proliferation and changes in the intercellular junctions, which affects monolayer permeabilityeq2 ref. , as comp9, the new analysis confirmed that the genes upregulated during the first hours after VEGFR-3 stimulation are to a large extent associated with transcription-related processes, including chromatin organization, RNA synthesis and stability. In addition to our previous analysis, we identified further TFs induced by VEGF-C156S, including FOXC2, ELK1, and NFATC1, which have been reported to regulate vascular development and angiogenesis before13–15. Importantly, our data also indicate that VEGFR-3 activation exerts direct anti-inflammatory effects on LEC, by downregulation of several immune- and cytokine-response associated genes. This is in line with the reported anti-inflammatory effects of VEGF-C on macrophages29 and indicates that VEGF-C, that has previously been found to reduce inflammation when applied in vivo30–32, not only acts via an increase of the lymphatic drainage, but also by inhibiting inflammatory signaling in LEC. Interestingly, these anti-inflammatory effects of VEGF-C are reminiscent of the effects of VEGF-A signaling in BEC34.In agreement with our previous analysis1. Nonetheless, VEGF-A and VEGF-C have been described to elicit different effects on lymphatic vessels in vivo, although the literature is not entirely consistent in this regard. For example, adenoviral delivery of VEGF-A into the ear of mice has been reported to induce massive dilation of lymphatic vessels35, whereas others found lymphatic dilation and formation of new lymphatic vessels only after delivery of VEGF-C, but not of VEGF-A36–38. This prompted us to attempt to identify genes differentially regulated by VEGFR-2 and VEGFR-3 within the same cell type, namely primary human LECs, by comparing our CAGE RNA sequencing data set of VEGF-C156S stimulated LECs with a microarray study of VEGF-A and wildtype VEGF-C stimulated LECs previously published by our group10. Naturally, cross-platform comparison of gene expression is problematic, due to inherent technical biases. Many studies have described a relatively good correlation between conventional RNA sequencing and microarray results obtained from the same starting material39–41. Similarly, CAGE RNA sequencing, in which only short (ca. 20 nt) 5’ fragments of mature, capped RNAs are analyzed, has been found to correlate well with conventional RNA sequencing42. Nonetheless, CAGE RNA sequencing is different from microarray and conventional RNA sequencing methods in that it does not assess the abundance of entire transcripts, but rather measures the activity of transcriptional start sites. Perhaps not surprisingly, a study comparing CAGE RNA sequencing directly with microarray and qPCR data found a rather low correlation between the data obtained by these techniques43. In our case, we additionally performed a cross-study comparison that likely introduced further bias due to biological differences in the starting material as well as experimental procedures and handling. Additionally, the data sets differed regarding the dosage of the growth factors applied: 1.5 μgml−1 in case of VEGF-C156S, 500 ngml−1 of wildtype VEGF-C, and 20 ng ml−1 VEGF-A. However, these doses reflect the differences in affinity and activity of the VEGFs, and are well within the range of what is commonly used by our lab and others45.VEGFR-2 and VEGFR-3 are structurally related and considered to activate similar intracellular signaling cascadesDespite these challenges, we observed the expected upregulation of an overlapping gene set after VEGFR-2 and VEGFR-3 stimulation with our approach, at least early after stimulation (60 min) when the induction of many downstream genes peaked. Furthermore, we identified several genes that were selectively regulated by stimulation of VEGFR-2 or VEGFR-3 only. These differentially regulated genes included the selective VEGF-A target genes RCAN1, ESM1 and ANGPT2. The specific induction of these genes by VEGF-A could also be validated experimentally, supporting the overall validity of our analysis. Selective upregulation of genes by VEGFR-2 might be explained simply by a difference in signal ‘strength’, e.g. due to higher ligand-receptor affinity, or higher kinase activity of the receptor, which are hard to control or manipulate experimentally. However, the fact that we also found a few genes regulated selectively by VEGFR-3 suggests that the quality of the signal downstream of the two receptors differs to some extent, e.g. by activating different kinases which in turn activate different TFs. Interestingly, stimulation with wildtype VEGF-C resulted in a ‘mixed’ response, with some genes being regulated as by VEGF-C156S and others as by VEGF-A.20. KLF4 is a direct transcriptional target of MAFB, a TF activated by VEGFR-3 signaling9, and may be involved in LEC differentiation by regulating the ‘master’ TF of LEC, PROX1  + 0.2% bovine serum albumine (BSA) over night and were subsequently incubated with 1.5 μgml−1 VEGF-C156S. RNA was extracted at 16 different timepoints  using TRIzol (Thermo Fisher) and subjected to CAGE RNA sequencing by the Fantom5 consortium at the RIKEN Institute  as described9. Raw counts were downloaded from the freely available Fantom5 data repository (http://fantom.gsc.riken.jp/5). CAGE peak expression analysis over the entire time course was done in R, using Bioconductor’s DESeq2 package . MA plots showing the log2FC compared to the average expression of the time point-specific CAGE peaks were done using the DESeq2 package. The corresponding genes  are provided in ‘Upregulated Genes after VEGFC156S stimulation’, ‘Downregulated Genes after VEGFC156S stimulation’, Data Citation 1. Heat maps and hierarchical clustering of the up- and downregulated genes were performed using Genesis .CAGE RNA sequencing data of primary human LECs stimulated with VEGF-C156S have been published previouslyhttp://geneontology.org, release 22.8.2016). GO biological process (BP) terms and molecular function (MF) terms with an adjusted P-value<0.01 were considered significantly enriched. The top 25 enriched GO terms (by fold enrichment) from each category were clustered manually into biologically related themes and are listed in ‘GO_BP analysis’ and ‘GO_MF analysis’, Data Citation 1.The DE genes were grouped into early (0 to 120 min), middle (150 to 240 min) and late (300 to 480 min) phase genes. Gene ontology (GO) enrichment analysis for each of these phases was performed using the Gene Ontology Consortium Database . RNA was extracted after 0 min (control), 60 min, 240 min, 480 min and 24 h, and subjected to microarray-based gene expression analysis using the Human Genome Survey V2.0 (Applied Biosystems) as described10. This data set has been deposited in the gene expression omnibus (GEO) repository under the accession number GSE11228 (Data Citation 2). Normalized data were retrieved and analyzed using the GEOquery package in Bioconductor, comparing the gene expression at the time points 60, 240 and 480 min to the 0 min (control) time point.Generation of gene expression data of primary human LECs treated with VEGF-A and wildtype VEGF-C has been published before2FC values at the matching time points 60, 240 and 480 min. To this end, we first removed all ambiguous CAGE peaks and probe sets. In the case of multiple peaks or probe sets associated with one gene, only the peak or probe set with the highest average expression was considered. Next, we used Entrez Gene IDs derived from corresponding annotation tables  to match the genes in the three data sets. Genes without available Entrez Gene ID in the corresponding annotation tables were additionally annotated using Bioconductor and the org.Hs.eg.db package (version 3.2.3) based on their gene symbol. The final matching of genes in the three data sets based on the Entrez Gene ID was done using R. From 16639 genes represented on the microarray, 10952 (at 60 min), 10951 (at 240 min), and 10989 (at 480 min) could be matched to the CAGE RNA sequencing data in this way. Log2FC values of all matched genes were plotted, and linear regression and correlation coefficients (Pearson) were calculated using GraphPad Prism V5. For the 3 time points, we selected genes differentially regulated by VEGF-C156S and VEGF-A if they were strongly regulated by either VEGF-A or VEGF-C156S (P<0.05 and log2FC>1 or <−1) and if there was at least a four-fold difference in the log2FC value after VEGF-C156S stimulation compared to the log2FC after VEGF-A stimulation .Comparison of the VEGF-C156S stimulation time course and the VEGF-A and VEGF-C stimulation time courses was done based on the log−1 VEGF-A (Cell Sciences), 500 ngml−1 mature wildtype VEGF-C (R&D Systems) or 1.5 μgml−1 recombinant VEGF-C156S . Total RNA was isolated using Genezol reagent (Geneaid) and extracted following the manufacturer’s protocol. The concentration of RNA was measured using a NanoDrop. Equal amounts of RNA were reverse transcribed using the High-Capacity cDNA Reverse Transcription Kit (Applied Biosystems). Gene expression of selected genes was quantified by qPCR using FastStart Universal SYBR Green Master (ROX) on a QuantStudio 7 Flex Real-Time PCR System (Applied Biosystems). RPLP0 was used as housekeeping control to normalize Ct values. Relative expression was calculated according to the comparative Ct method. Primer sequences are listed in 24 h before stimulation, 70000 primary LECs were seeded on collagen type-I coated 12-well plates. Next, LECs were starved over night in EBM + 0.2% BSA and were subsequently treated for 60, 240 or 480 min with 20 ngmlHow to cite this article: Dieterich, L. C. et al. Distinct transcriptional responses of lymphatic endothelial cells to VEGFR-3 and VEGFR-2 stimulation. Sci. Data 4:170106 doi: 10.1038/sdata.2017.106 (2017).Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


However, this metric failed in overall survival (OS) prediction. In the present proof of concept study, we aimed to explore the prognostic value of intratumoral textural features (TF) as well as volumetric parameters  derived by pre-therapeutic 18F-FDG PET.The metabolically most active lesion in 2-deoxy-2- mutational status) for prediction of both PFS and OS were evaluated.Eighteen patients with progressive MTC underwent baseline P = 0.03). Baseline TLG designated 11/18 patients to the high-risk group . The Hazard Ratio for cancer-related death was 6.1 for Complexity . Among investigated clinical parameters, the age at initiation of TKI treatment reached significance for PFS prediction .The TF Complexity and the volumetric parameter TLG obtained at baseline prior to TKI initiation successfully differentiated between low- and high-risk patients. Complexity allocated 10/18 patients to the high-risk group with an OS of 3.3 y (vs. low-risk group, OS = 5.3 y, 8/18, AUC = 0.78, The TF Complexity and the volumetric parameter TLG are both independent parameters for OS prediction. The tyrosine kinase inhibitor (TKI) vandetanib, a selective inhibitor of wild-type rearranged during transfection (RET) kinase as well as of vascular endothelial growth factor receptor (VEGFR) signaling –3, has d18F)fluoro-D-glucose (18F-FDG) positron emission tomography (PET) has been demonstrated as a useful tool for outcome prediction in various tumor entities, including salivary gland carcinoma, pancreatic cancer, and colorectal cancer   , 25. Allimmediate next voxel. Higher-order parameters are calculated from 3-dimensional neighborhood gray-tone (intensity) difference matrices (NGTDM) to describe local features. These parameters are based from differences between each voxel and the neighboring voxels in adjacent image planes: The NGTDM (M4) contains entire homogeneous areas of a certain intensity and size [The following TF, which had been investigated in a previous study for outcome prediction in non-small cell lung cancer (NSCLC) patients under TKI treatment , were inand size . Higher-and size .To assess the entire baseline tumor burden, 109 metastases  were initially segmented. After treatment initiation with vandetanib, 56 metastases  at follow-up were still available for segmentation. Details on segmented VOI for both baseline and follow-up PET are given in Supplementary Table Serum levels of carcinoembryonic antigen  and calcitonin  were measured (prior to baseline imaging with a median of 6 determinations) . Tumor mP value < 0.05.Statistical analysis was performed using Medcalc (Vers. 17.4.4). The cutoff values of each parameter for PFS and OS prediction were determined by receiver operating characteristic (ROC) analysis (with the Youden-Index for maximization of specificity and sensitivity) (23). Kaplan–Meier analysis  was performed using thresholds established by ROC analysis in cases in which ROC showed statistically significant results. A multivariate Cox hazard analysis was conducted to determine independent prognostic parameters . Additionally, Hazard Ratios (HR) were obtained. Statistical significance was considered with a 18F-FDG PET was positive in the entire cohort, with 17/18 (94.4%) patients presenting with lymph node involvement and 10/18 (55.6%) with lung metastases. 9/18 (50.0%) patients had liver lesions, 9/18 (50.0%) had bone lesions, 2/18 (11.1%) had soft tissue metastases, and a single subject  suffered from infiltration of the pancreas . Median follow-up was 6.4 years . 12/18 (66.7%) patients experienced progressive disease after a median of 2.6 y , whereas the remaining 6 patients remained stable. Nine out of 12 progressive disease patients died of their disease  after a median of 4.1 y .18F-FDG PET, follow-up PET and change in % between both scans). Besides for Homogeneity, all investigated parameters demonstrated a decline between succeeding scans.The mean (range) values for all investigated PET parameters are given in Table P = 0.03; PFS, P = 0.07). Moreover, Contrast of >11.2 at baseline  was also correlated with significantly reduced PFS of 0.8 y .Complexity of > 59 at baseline  correlated with significantly reduced OS of 3.3 y , AUC = 0.78, P = 0.005; PFS, P = 0.11).Among the analyzed volumetric parameters, TLG > 2694 at baseline  was correlated with significantly reduced OS of 3.5 y (vs. <2694 in 7/18 (38.9%), OS = 5 y, AUC = 0.83, None of the investigated delta parameters reached significance in ROC analysis. Table p = 0.04). For OS, baseline TF Complexity and baseline TLG reached significance .To determine independent prognosticators, a subsequent multivariate Cox analysis was performed: for PFS, baseline TF Contrast was found to be significant .For those subjects above the ROC-derived threshold, the HR for Complexity was 6.1 for OS . Similar results could be obtained for the TF Contrast for patients above the threshold: HR was 3.7 (1.1–12.2) in terms of PFS . For the volumetric parameter TLG, the HR was 9.5  for OS . Among investigated clinical parameters, the age at initiation of TKI treatment demonstrated significance for PFS prediction (p = 0.02). For OS, baseline TF Complexity (p = 0.006) and baseline TLG (p = 0.008) reached significance. Respective Kaplan–Meier Plots for selected parameters  are displayed in Fig. Using ROC-derived cutoffs, Kaplan–Meier analysis found a significant separation between high- and low-risk groups for baseline TF Contrast . These findings were further corroborated by obtaining an HR > 6 for cancer-related death for those subjects above the ROC-derived threshold. Similar results were observed for the volumetric parameter TLG: a higher glucose consumption by the tumor volume at baseline was also independently associated with shortened OS  have been investigated for outcome prediction, e.g., in NSCLC treated with the TKI erlotinib [max [max at baseline, 3.4–19.9 vs. SUVmax at baseline in the study of Cook et al., 1.2–30.1 [Changes in PET features for TKI response assessment and survival prediction have been evaluated in numerous previous studies. However, primarily SUV parameters automatic lesion detection software: this might pave the way for a cost-effective and time-saving implementation of TF assessment in clinical routine in the long run . Future The TF Complexity and the volumetric parameter TLG, obtained from baseline PET, are both independent parameters for OS prediction in MTC patients scheduled for TKI treatment. Further investigations using intra-tumoral heterogeneity for risk stratification and prognostication are warranted, particularly in patients suffering from tumor entities treated with TKI.Supplementary Material


Behavioral responses to novel situations often vary and can belong to a suite of correlated behaviors. Characteristic behaviors of different personality types (e.g. stress coping styles) are generally consistent across contexts and time. Here, we compare the repeatability and reliability of exploratory behaviors between zebrafish strains selectively bred to display contrasting behavioral responses to stressors that represent the proactive-reactive axis. Specifically, we measure exploratory behavior of individual fish in an open field test over five weeks. We quantified the stationary time, average swimming speed and time spent by a fish in the center area. We found a number of strain differences for each behavioral measure. Stationary time was the most repeatable and reliable measure for assessing proactive-reactive behavioral differences. Reactive zebrafish generally showed the highest reliability and repeatability of exploratory behavior compared to proactive zebrafish and a separate wild caught strain. Given the increased interest in the evolutionary consequences and proximate mechanisms of consistent individual differences, it will be important to continue to investigate how different selective pressures may influence expression of stress coping styles and their effects on the consistency of an animal’s behavior. In response to stressors, many studies document consistent differences between individuals across contexts in behaviors like aggression, boldness and sociability but the temporal component within the same context has not been thoroughly examined8.Animals are frequently faced with a variety of stressors to their survival and reproductive efforts and typically employ behavioral and physiological responses to overcome them. While an individual’s behavioral response has been thought to be labile in variable environments, studies show that it can be consistent. Consistency of behavioral and physiological responses have both a between and within-individual component where the response in one context is often predictive of the animal’s response in a disparate context and across time10. Proactive individuals are characterized by actively engaging stressors, having a feed-forward memory process, low glucocorticoid stress response, and low behavioral flexibility. In contrast, reactive individuals are more sensitive to environmental cues with reduced exploration of novel environments, a higher glucocorticoid stress response, and higher behavioral flexibility10. Both coping styles represent adaptive responses to environmental challenges and are maintained within a population due to fitness trade-offs in a variable environment13. Selective pressures such as predation and immune challenge can constrain behavioral variation within a population and strengthen correlations between traits, thereby facilitating correlated behaviors and physiology16.Across many taxa there are two alternative correlated suites of behavioral and physiological responses to stressors known as proactive and reactive stress coping styles17. Few studies have investigated repeatability  and reliability  of behaviors in stress coping styles across multiple time points. Studies looking at aggressive behavior of selectively bred mice (Mus musculus) suggest that proactive individuals with low behavioral flexibility show greater reliability across trials than reactive individuals19. Similarly, proactive great tits (Parus major) establish more rigid routines during an open field test (OFT) and novel object test while reactive birds showed a higher degree of behavioral plasticity and lower reliability20. While some studies report conflicting results in teleosts22, selectively bred reactive trout (Oncorhynchus mykiss) display higher behavioral flexibility when a novel object was introduced during a feeding task23. Despite these observations, the repeatability and reliability of stress coping styles across time has not been well-established. Further, it is also not well understood how artificial selection may affect repeatability and reliability of behavior.Selectively bred strains of proactive and reactive behavioral phenotypes are often used to investigate the proximate mechanisms of stress coping styles and estimate heritability26. Within-individual variation of exploratory and other behaviors over time are influenced by factors such as prior experience, age, and motivation8. To investigate within-individual consistency across time, studies have used the reliability estimate, which measures the predictability of an animal’s performance on a measured variable over time relative to others within a population . In human and animal personality studies, reliability estimates tend to range between 0.7–0.8527. A frequently used estimate to measure consistent differences between individuals is repeatability. The repeatability of a behavior is defined as the intraclass correlation coefficient and is calculated as the ratio of between-individual variance and the sum of between- and within-individual variance. Overall, exploratory behavior in a novel environment is repeatable in many avian, rodent, and teleost species with repeatability values ranging from 0.2–0.530. In addition to exploratory behavior, other behaviors such as thigmotaxis and movement speed have been commonly used to assess the magnitude of behavioral stress response and could also be indicative of an individual’s stress coping style32. Thigmotaxis and movement speed are generally repeatable like exploratory behavior33. It is unknown which behavior  is most suitable for use as an indicator of an individual’s stress coping style.Exploratory behavior in a novel environment can be used to assess the magnitude of a stress response and categorize an individual into a stress coping style. Variation in exploratory behavior is widely studied and often utilizes the well-established OFTDanio rerio) are a promising teleost system to understand the causes and consequences of correlated behavioral variation35. Both wild and laboratory strains of zebrafish display the proactive and reactive stress coping styles, and have distinct and heritable genetic architectures42. Proactive zebrafish are typically dominant and have higher reproductive success44. We have previously shown that selectively bred proactive and reactive zebrafish strains show consistent behavioral differences across a variety of contexts between the strains41. Additionally, artificial selection of exploratory behavior will constrain morphological evolution and glucocorticoid responses45. While the consistency of exploratory behavior has not been extensively studied in individual strains of proactive and reactive zebrafish, several studies have suggested that other boldness, aggression, and locomotor behaviors are generally consistent across contexts and time, and are influenced by selective pressures48. Thus, zebrafish can provide unique insights into underlying mechanisms of behavioral variation in coping with stress and subsequently how variation can be constrained by selective forces acting on populations.Zebrafish  exploratory behavior is stable across time, (ii) repeatability and reliability measures differ between the stress coping style strains, and (iii) selectively bred strains are more repeatable or reliable than a separate wild caught population. By measuring variation of behavior within and between individuals, we can gain insight into factors contributing to the emergence and maintenance of stress coping styles in different populationsDanio rerio) strains: wild caught (WC), high stationary behavior (HSB), and low stationary behavior (LSB). Wild caught fish were imported from North Bengal, India through a commercial supplier  and housed in the laboratory for 21 months before testing. The HSB and LSB strains were selected for stationary behavior (i.e. exploratory behavior) in an open field test and were 10 generations removed from a wild caught population from Gaighata in West Bengal, India41. The HSB and LSB strains display behaviors across multiple different behavioral assays, glucocorticoid responses, and morphology consistent with the reactive and proactive stress coping styles, respectively54. Additionally, HSB and LSB strains differ in neurotranscriptome profiles55. Females of both strains exhibit higher stationary time than males in an open field test56. We tested 28 individuals from LSB  and 27 each from HSB  and WC strains . LSB and HSB individuals were 13 months post-fertilization when testing began. Fish were individually housed in 3-liter tanks throughout the period of experiments on a recirculating water system (Pentair Aquatic Eco-Systems) using UV and solid filtration. Water temperature was set at 27 °C. Fish were kept on a 14:10 L/D cycle and fed twice a day with Tetramin Tropical Flakes . Morning feedings were prior to experiments on testing days.We used three different zebrafish  was filled with 4 L of system water. Animals were individually placed in the arena and video-recorded for 5 min. Each fish was tested once a week for five consecutive weeks between 8 and 10 h in the morning. The video recordings were analyzed with Noldus EthoVision XT . For each fish, we quantified three estimates of exploratory behavior: stationary time, average swimming speed and time spent in the center. The subject was considered stationary if it was moving less than 0.5 cm/s and the center zone was defined as the 15 × 15 cm zone in the center of the chamber. We digitally measured standard length of each fish at end of the five weeks. There was a significant effect of strain on standard length . The WC strain (3.27 ± 0.05 cm) was significantly larger than the HSB  and LSB lines . HSB and LSB lines did not significantly differ in standard length (p = 0.42). Females (3.03 ± 0.04 cm) were significantly larger than males . All testing experiments were approved by the Institutional Animal Care and Use Committee of University of Nebraska at Omaha/University of Nebraska Medical Center  and were performed in accordance with the relevant guidelines and regulations.To test the repeatability and reliability of exploratory behavior, we used the open field test following established procedures57.Reliability of exploratory behavior across time and between-strain differences were tested using a repeated measures general linear model (GLM) in SPSS (Version 24). Sex and strain were included as between-subjects variables and standard length was controlled for by including it as a covariate. Since the assumption of sphericity was violated for each of the three exploratory behaviors we applied the Greenhouse-geisser correction. This did not change any statistical conclusions, therefore we only reported the uncorrected model. For the post-hoc comparisons of the estimated marginal means of the three estimates of exploratory behavior, we applied a Benjamini-Hochberg correction to reduce the likelihood of type I errors58. This allowed us to control for shared associations between the behaviors in a single model, and more importantly test for differences in the variability within- and between-individuals across strains. First, we began with an unconditional model to assess the variability at each level . Next, the covariances between all the behaviors were included at each level. Then, we split the models by strain  and constrained every part of the model in a step-wise fashion to ascertain which sources of variability were significantly different across the strains . A constraint was considered to have worsened the model based on a significant chi-square test (p < 0.05). Any significantly worsening constraint reflects a difference in the estimates between strains.To assess behavioral variation among strains, we used multilevel structural equation modeling in M-plus statistical analysis software59. We calculated R based on variance components estimated from the multilevel structural equation model. Based on several literature meta-analyses61 we describe repeatability values as follows: low repeatability R ≤ 0.2; moderate repeatability 0.2 < R < 0.4; and high repeatability R ≥ 0.4. Reliability measures were estimated as the inter-trial reliability measure in SPSS (Version 24). Values > 0.8 were considered highly reliable and indicate that individuals maintained rank order across the five weeks of testing. Of note, repeatability and reliability values are deemed significantly different from a comparison value if they do not fall within that comparison value’s 95% confidence interval. All statistical tests were two-tailed, and were conducted with an alpha level of 0.05.Repeatability was defined as the intraclass correlation coefficient (R), which was calculated as the ratio of between-individual variance and the sum of between- and within-individual variance2,79 = 15.75 p < 0.01, Table 2,79 = 3.37 p = 0.04, Table 2,79 = 40.73 p < 0.01, Table There was a significant between-subjects effect of strain for stationary time  and week*standard length  for time spent in the center . The resulting model provided adequate fit (χ2(3) = 1.15, p > 0.05, CFI = 1.00, RMSEA < 0.01, SRMR(within) < 0.01, SRMR(between) = 0.10). After constraining the variability at the within-individual level, a number of differences emerged , both of the LSB (R = 0.56) and HSB (R = 0.71) strains showed high repeatability values for stationary time (Table 15. Field crickets (Gryllus integer) exposed to a common bacterial pathogen showed increased repeatability in their tendency to explore a novel environment15. Similarly, boldness and aggression behaviors were correlated in wild sticklebacks (Gasterosteus aculeatus) only after exposing the population to predation14. In great tits, correlation between exploratory behavior and stress physiology emerged through selectively bred proactive and reactive birds but not wild individuals62. These studies suggest that selection can influence expression of repeatability and reliability by potentially placing survival costs on individuals. Predation has frequently been identified as one of the strongest ecological pressures that can influence the repeatability and reliability of animal behavior47. We speculate that by selecting for an ecologically relevant behavioral response to a stressor in the HSB and LSB lines within the lab, it may have been simulating selection of behavioral responses to predation in the wild. Low exploratory behavior may be adaptive and directly selected for in environments with high predation. This could explain why the HSB fish showed the highest repeatability and reliability values for a majority of the behavioral estimates. Altogether, this indicates that artificial selection may act similarly to natural selection and increase the repeatability and reliability of behavior.High exploratory behavior in a novel environment is characteristic of the proactive stress coping stylele R = 0.9, both ome Table . Further64. Despite being a measure of stress and type of exploratory behavior, thigmotaxis has not been commonly used to predict an animal’s stress coping style. We observed that the repeatability of time in the center in the HSB, WC, and LSB strains was high, low, and not repeatable, respectively . Behavioral correlations appeared and disappeared across years that coincided with changes in the density and age composition of the bird population, which could reflect changes in resource availability65. Our results suggest that the ecological pressures acting on the WC population shaped different behavioral patterns compared to those resulting from artificial selection.It should be noted that the WC individuals were imported from North Bengal, India, which is a different location than the founding animals used to generate the HSB and LSB strains . The local ecological factors that might have contributed to shaping the WC animals’ behavior are not known. It is possible that some population differences or behavioral correlations may only emerge under certain local environmental conditions66. There were no significant differences between the HSB and LSB strains in standard length or mean swimming speed. Although a previous study showed that the LSB strain swims faster and has a larger caudal region compared to the HSB strain, this was examined using morphometrics and within a startle-response paradigm31. Measuring standard length does not allow for inferring size of specific body areas . In our study we also measured average swim speed over a five minute period within the open field test and did note evoke a startle-response. All three strains were highly repeatable for average swimming speed 33. There was no effect of time across weeks  and selectively bred traits .Previous studies suggest that proactive individuals with low behavioral flexibility and rigid behavior patterns are more consistent than reactive individualsks Table . Furtherks Table . It is p7. In studies examining repeatability and reliability within a social context such as aggressive behaviors19 and predator inspection68, it is difficult to ensure consistency of behaviors and motivation of live stimulus animal across trials. Thus, the context the focal animal experiences may subtly vary across testing periods and make it difficult to understand if results are due to stimulus animal behavioral state or within-individual variation over time. In using the OFT we removed potential confounds of varying contexts over time and therefore are confident we measured within-individual variation. Even when these changing contexts are taken into account, other internal developmental factors can also influence the repeatability and reliability of behavior. Despite using a similar methodology as the current study, selectively bred proactive great tit birds were more consistent over time in exploratory behavior relative to the reactive birds20. It is noteworthy that the two assay time points were across developmentally distinct periods (once in juveniles and once in adults), which has been shown to influence repeatability60. In the current study, all zebrafish were sexually mature adults at the time of testing and were assayed over five weeks, which could explain the inconsistency of our findings.It is also important to be able to separate out changes in consistency across time from those that could be due to changes in contexts between assay time points69. This is especially important given that a central assumption of stress coping styles is that a behavioral phenotype is maintained over time, despite the observation that animal behavior can be very labile over small durations61. Here, we found that stationary time was the most repeatable and reliable estimate of exploratory behavior over five repeated observations. Additionally, the artificially selected proactive and reactive strains showed higher repeatability and reliability values compared to the wild caught population. This suggests that in populations under high levels of selection, a single to a few measurements for the examined behaviors can be a sufficient representation of that individual’s behavior. While increasing the number of repeated trials allow for more robust repeatability estimates, short inter-trial intervals can lead to habituation or other forms of associative learning. These types of learning can have confounding effects on estimates of repeatability and reliability70. If animals habituate during repeated measurements, there is weaker construct validity of assessing consistency of stress coping behaviors. We found no evidence of habituation in our study with a one week intertrial interval (Fig. There are many key considerations when estimating repeatability and reliability of animal behavior. Often studies have estimated repeatability by using two measurements for each individual, which can overlook any behavioral changes that may occur over longer periods of time or multiple observationsDataset 1


The aim of this study was to explore the relationship between compliance with preoperative posturing advice and progression of macula-on retinal detachment (RD) and to evaluate whether head positioning or head motility contributes most to RD progression.Sixteen patients with macula-on RD were enrolled, admitted to the ward, and instructed to posture preoperatively. The primary outcome parameter was compliance, which was defined as the average head orientation deviation from advised positioning. Secondary outcome parameters included the average rotational and linear head acceleration. The head orientation and acceleration were measured with a head-mounted inertial measurement unit (IMU). Optical coherence tomography (OCT) imaging was performed at baseline and during natural interruptions of posturing for meals and toilet visits to measure RD progression toward the fovea.P = 0.001, rs2 = 0.13) for compliance, 0.52  for rotational acceleration, and 0.49  for linear acceleration. The correlation coefficient between RD progression and rotational acceleration was statistically significantly higher than the correlation coefficient between RD progression and compliance (P = 0.034).The Spearman correlation coefficient with RD progression was 0.37 (The strength of the correlation between RD progression and compliance was moderate. However, the correlation between RD progression and rotational and linear acceleration was much stronger. Preoperative posturing is effective by reducing head movements rather than enforcing head positioning.Monitoring the efficacy of preoperative posturing in macula-on RD using OCT and IMU measurements shows that a new and combined application of these technologies leads to clinically relevant insights. Retinal detachment (RD) is a progressive separation of the retina from the underlying retinal pigment epithelium that occurs in 12 to 18 per 100,000 people per year.36Compliance with positioning advice has been quantified previously using gravity- and tilt-compensated sensors after macular hole surgery.15The primary aim of this study was to explore the relationship between compliance with the preoperative posturing advice and the progression of macula-on RD. The secondary objective was to evaluate whether head positioning or head motility contributes most to the progression of RD.www.trialregister.nl identifier, NTR4884). The study evaluated a small cohort that was enrolled in addition to a larger prospective trial evaluating preoperative posturing.This study was designed as an explorative cohort study with recordings of head orientation, head motility, and the distance between the RD border and fovea during preoperative posturing of patients with macula-on RD. The study was approved by the local internal review board of the Rotterdam Eye Hospital and the medical ethical committee of the Erasmus Medical Center, Rotterdam, The Netherlands  and within the range of the OCT system (estimated range was up to 10–12 mm from the fovea); sufficiently clear media to obtain an OCT scan; sufficient quality of the OCT scan; and OCT performed within an hour after admission of the patient to the ward. No exclusion criteria were specified. The safety border of 1250 μm from the foveola was defined by the traditional size of the fovea centralis (with a radius of approximately 750 μm) and parafovea (ring of 500 μm around the fovea) combined.19Within 1 hour after arrival on the ward, a baseline volume OCT scan  was performed, and eligibility was determined. The distance between RD border and fovea was measured according to our previously described method.Measuring eye saccades over longer periods of time is not possible without invasive measures. However, measuring head orientation and motion is possible in a noninvasive manner by using a head-mounted electronic sensor, the Shimmer3 inertial measurement unit (IMU) . This IMU is small, lightweight, commercially available, and CE-marked, which indicates conformity with several health and safety regulations within the European Economic Area. After eligibility of a patient was determined, the IMU was fixed on the forehead of the patient with hypoallergenic, waterproof, and strongly adhesive plasters.X-axis points toward the north, the Y-axis toward the west, and the Z-axis up, perpendicular to the earth's surface. To prevent gimbal lock, quaternions were used instead of Euler angles to describe the three-dimensional rotations. The quaternions were calculated using the Shimmer Matlab Instrument Driver software (Shimmer Sensing), which estimates orientation data using magnetic angular rate and gravity (MARG) filtering. MARG filtering is reported to achieve orientation accuracy levels with less than 0.8° static error and less than 1.7° dynamic error.19We configured the IMU to use three individual sensors: a low-noise accelerometer, a gyroscope, and a magnetometer at a 512-Hz sampling rate. The IMU was calibrated according to the north-west-up coordination system, which means that the The primary outcome parameter of the IMU was defined as the orientation deviation from the advised positioning. We considered three secondary outcome parameters: the orientation deviation from the (presumed) optimal positioning, the rotational acceleration, and the linear acceleration.To obtain the deviation from the advised positioning, we used the relative (inverse) direction of gravity measured by the IMU at each time point. At the beginning of the first posturing interval, when the patient was positioned according to the advice, we determined the reference orientation of gravity . SubsequPositioning is mostly prescribed in four categories: supine, temporal side, nasal side, and upright. This advice does not account for the distance between the fovea and the RD border or the precise location of the closest point on the RD border. For instance, positioning on the temporal side might be optimal for peripheral temporal RD, but a temporal RD that already has progressed close to the fovea might be better positioned supine to support reattachment of the retina closest to the fovea. Patients with inferior temporal RD might be better positioned with half-upright on the temporal side instead of a choice between temporal side or upright. We hypothesize that in optimal positioning the gravitation forces are directed perpendicular to detached retina that is closest to the fovea to facilitate reattachment of this part of the retina see . DetermiAccelerations around the X-, Y-, and Z-axes, both clockwise and counterclockwise, were all assumed to be equally relevant and included in the analysis. To obtain the rotational acceleration, the rotational velocity of two consecutive time points were subtracted from each other and divided by the time difference for all gyroscope axes separately. The total rotational acceleration was then defined by the root mean square of the rotational acceleration of the three axes.To obtain the residual linear acceleration, we first corrected the measured linear acceleration for gravity. The total linear acceleration was then estimated by the root mean square of the residual linear accelerations obtained with the three accelerometer axes.Because of the various durations of posturing and interruption intervals, the average of IMU parameter per interval was expected to provide the most consistent comparison to the average RD progression velocity per interval. The measured signal was corrected for the noise floor levels as seen during static test measurements and during the posturing intervals of the patient measurements.2 at increments of 250°/s2 and the linear acceleration thresholds between 0.25 and 10 m/s2 at increments of 0.25 m/s2.We additionally wanted to determine whether head movements in general should be avoided by patients or whether sudden head movements with fast accelerations in particular should be avoided to prevent RD progression. Therefore, we determined the number of rotational and linear accelerations per interval per hour above a specific threshold and calculated the correlation with RD progression. We varied the threshold levels to evaluate whether higher thresholds would result in stronger correlation coefficients than the correlation coefficients between RD progression and the noise-corrected averages of IMU parameters. We varied the rotational acceleration thresholds between 250° and 10,000°/sU test) was used to compare RD progression and IMU parameters between posturing and interruption intervals. We expected a monotonic but possibly nonlinear relationship between RD progression and the IMU parameters. Therefore, Spearman's correlation coefficient was calculated to describe the relationship between RD progression and average IMU parameters. The correlation analysis was performed for all measured intervals as well as for the progression from baseline. For all IMU parameters, a positive correlation demonstrates an association with RD regression and a negative correlation an association with RD progression. Statistical significant differences between correlation coefficients were tested according to the methods of Meng et al.Due to the exploratory nature of this study, 16 patients with continuous measurements between admission to the ward and surgery were assumed to be sufficient to show general trends. We did not assume normally distributed data, and therefore nonparametric testing . All patients provided a written informed consent. Patients' characteristics are summarized in P = 0.003). The median RD border displacement velocity during posturing intervals was −1 μm/h (IQR: −9 to 34 μm/h) and during interruptions −202 μm/h (IQR: −491 to 0 μm/h), which was statistically significantly different as well (P < 0.001).A summary of the RD progression measurements is provided in 2 for rotational acceleration, and 0.8 m/s2 for linear acceleration. The difference between posturing intervals and interruptions was statistically significant for all four IMU parameters (P < 0.001).The average IMU parameters for all posturing and interruption intervals, as well as the intervals from baseline, are described in rs) between RD progression and the IMU parameters were found for rotational acceleration (rs = 0.52) and linear acceleration (rs = 0.49). The rs2 can be interpreted as a proportion of explained variance if the IMU parameters and the RD progression are presented as ranked variables. The higher this proportion, the more variance is explained by a specific variable. The rs2 was 0.13 for orientation deviation from the advised positioning, 0.13 for the orientation deviation from optimal positioning, 0.27 for the rotational acceleration, and 0.24 for the linear acceleration. This means that rotational acceleration as well as linear acceleration seems to explain twice as much of the variance of RD progression than orientation deviation from advised or optimal positioning. The correlation coefficient between RD progression and rotational acceleration was statistically significantly higher than the correlation coefficient between RD progression and compliance  for orientation deviation from optimal positioning, 0.68 (rs2 = 0.46) for rotational acceleration, and 0.72 (rs2 = 0.49) for linear acceleration. This means that the secondary IMU parameters are codependent with the primary IMU parameter (orientation deviation from advised positioning), but they are not the same.The Spearman's correlation coefficient between orientation deviation from advised positioning with the other three IMU parameters was 0.52 .The average head orientation deviation was not significantly correlated with RD progression from baseline see , row 2. P = 0.76).The correlation between the duration of follow-up and the change of RD-fovea distance from baseline to the last OCT measurement was 0.08  to minimize the amount of head and eye movements. Previous research showed that a reduction of eye movements (saccades) by double patching the eyes or suturing the eye muscles to the bulbus resulted in a reduction of subretinal fluid.6Several other factors may affect RD progression. Most importantly, we measured head movements, whereas saccades are traditionally expected to be able to overcome the forces of retinal adhesion.23There are at least four other factors that may play a role in RD progression. Firstly, the retinal adhesion strength differs between retinal locations and is especially higher at the macula. It is a common observation among surgeons that the peripheral retina detaches much more easily than does the posterior retina when creating a RD for macular rotation or retinal pigment epithelium–choroid graft, suggesting a difference in adhesion.33Evaluation of the orientation deviation from optimal positioning did not reveal a stronger correlation with RD progression than did the orientation deviation from advised positioning. This suggests that the optimization of positioning would not significantly reduce RD progression. It also suggests that the role of gravity is limited, which is expected because the density difference between the retina and subretinal fluid is small.18Evaluation of the number of accelerations per interval above various thresholds did not reveal a substantially higher correlation with RD progression than did the average of IMU parameters per interval. This might indicate that relatively slow head accelerations are also able to induce RD progression, or it might be that patients did not frequently perform sudden head movements during their hospitalization and the number of fast head accelerations was too low to reveal a stronger relationship. We cannot conclude that only strong or sudden head movements should be avoided. Evaluation of the relationship between the duration of follow-up and the change of RD-fovea distance from baseline did not reveal a statistically significant relationship. As pointed out above, RD progression can be explained by other factors only than the duration of follow-up.Our method by which we measured head orientation might be used, in combination with OCT distance measurements, to evaluate the effect of delayed surgery for 1 day with preoperative posturing at home. This alternative policy might be cost saving for both clinics that aim to provide 7 days per week surgery service and clinics that hospitalize patients preoperatively. However, such a study should take into account the expected differences in characteristics and behavior between hospitalized patients and patients who are asked to stay quiet at home. IMU devices might also be used for other areas of ophthalmology where the effect of posturing regimes warrants validation, such as postoperative positioning after macular hole surgery,15Strengths of this study include the objective measurements of head orientation, head movements, and RD progression and the reasonable amount of 78 monitored intervals. Limitations include the small number of patients, the variation in RD localization and subsequent positioning advice, and the differences in follow-up duration. In addition, the patient might have touched the device causing false rotational and linear accelerations. Since this would result only in short acceleration peaks, we think that the influence on the averages and number of accelerations per interval is small.In conclusion, preoperative posturing advice should emphasize a reduction of head movements, although positioning might be beneficial to prevent RD progression as well. This study may be an important step toward an evidence-based policy for optimal preoperative posturing in patients with macula-on RD.Supplement 1Click here for additional data file.Supplement 2Click here for additional data file.


With the increase of Qatar’s total population, primarily due to the influx of healthy male migrant labor, worldwide attention has been focused on deaths among these migrant workers.To describe adult mortality trends in Qataris  and non-Qataris (migrants) from all causes, cardiovascular and circulatory disease, neoplasms, and injuries, 1989–2015.We retrieved Qatar’s vital registration data by nationality, sex, age group, year, and codes of the World Health Organization’s International Classification of Diseases, Ninth and Tenth Revisions. We assessed age-standardized mortality rate (ASMR) trends in Qatar’s total population, in Qataris and non-Qataris using Joinpoint regression.During the study period, 26,673 deaths were recorded. In 2015, we estimated 60,716 years of life lost  in the overall population. In Qataris (both sexes) and in non-Qatari females, all-cause rate decreased significantly and steadily between 1989–2015. In non-Qatari males, it decreased significantly between 1998–2010 probably attributed to a massive influx of healthy migrants. Yearly rates were significantly lower in non-Qataris over 27 years. Reduction in Qatar’s total population rates for all causes and for neoplasms can be partially attributed to the healthy migrant effect. For injuries in males, it was lower in non-Qatari. Remarkably, for falls, cause-specific ASMR in non-Qatari males decreased significantly reaching 2.6/100,000 in 2014, suggesting improved safety in the work environment. However, while young adult males in Qatar die predominantly from injuries, young adult females die from neoplasms.Our study demonstrates that premature death in young adult males and females in Qatar is predominantly due to injuries and neoplasms respectively. These identified causes of death are for a large part preventable and should be addressed appropriately to lower premature mortality among young adults in Qatar. The major contributor to Qatar’s total population growth has been the influx of healthy male migrant labor  to buildParallel to the demographic challenges, Qatar is grappling with high rates of diabetes and obesity. Qatar is among the top ten countries with the highest diabetes prevalence worldwide , at 17% For assessing the impact of demographic changes, socioeconomic and healthcare system development, and health-based interventions, measuring the magnitude of deaths by population is necessary. Therefore, we evaluated trends over 27 years of all-cause mortality and cause-specific mortality for the three commonest causes of death, namely cardiovascular and circulatory disease, neoplasms, and injuries, in Qataris and non-Qataris . Additio20–29, 30–39, 40–49, ≥50), year (from 1989 to 2015), nationality (Qatari/non-Qatari), and codes of the World Health Organization’s (WHO) International Classification of Diseases, Ninth and Tenth Revisions (ICD-9 and ICD-10) were retrieved [In order to estimate mortality rates in Qatar’s total population, in Qataris and non-Qataris between 1989–2015, we retrieved vital registration data from the Qatar Vital Statistics Annual Bulletins of the Ministry of Development Planning and Statistics (MDPS). Grouped secondary data, which are publicly available on the Ministry’s website  were useetrieved , 24. We etrieved , which aPublicly available data on Qatar’s yearly population size by sex, five-year-age group (from 15 year old to over 75 year old), and nationality were retrieved from MDPS’s Census, Population, Housing, and Establishments annual reports for the years 2006–2014 . Annual Age-standardized mortality rates  and corresponding standard errors were estimated using the direct method  and the p)-value threshold = 0.05). We provided contextual information that could explain all-cause mortality trends in Qataris and non-Qataris by reporting pertinent dates that marked Qatar’s socioeconomic and healthcare system development [Estimated ASMRs and their standard errors were imported into the United States Surveillance, Epidemiology, and End Results Joinpoint Trend Analysis Software (version 4.4.0.0) . Using Jelopment , 32.In order to identify significant differences in all-cause mortality between Qataris and non-Qataris, we estimated Comparative Mortality Figures (CMFs), which correspond to the ratio of ASMR in Qataris divided by the ASMR in non-Qataris . We alsoDuring the study period, 26,673 deaths in over-20-year-old adults were recorded . Deaths in males were 2.7 times more frequent than in females . The annual average number of all-cause deaths was 1,159 deaths ranging from 632 (1989) to -2,070 (2014). In non-Qataris, annual total number of deaths increased about four-times, from 296 deaths (1989) to 1,438 deaths (2015). In Qataris, annual total number of deaths also increased but at a lower magnitude as compared to non-Qataris (from 336 deaths in1989 to 560 in 2015). In 2014, in Qatar’s total population, injuries were responsible for 19.7% of deaths , followed by cardiovascular and circulatory disease 17.8% , and neoplasms 15.8% .In 2015, we estimated 60,716 YLL  in Qatar’s total population . In 2014p-values<0.05). Even if ASMR decreased two-times faster in Qataris than in non-Qataris, all-cause ASMRs in Qataris were always significantly higher than in non-Qataris . However, the magnitude of the ratio decreased over time (both sexes). Thus, all-cause ASMR in Qatar’s total population was always lower than in Qataris because of the mortality rates in non-Qataris, which includes mainly migrant workers. Overall, healthy worker effect seems to influence ASMR trends in Qatar’s total population.Between 1989–2015, all-cause ASMR  significantly decreased in non-Qataris ; and in Qataris . In non-Qatari females, the decreasing trend was steady since 1989 but at a slower pace . This decrease in mortality appears to follow Qatar’s gradual healthcare system and socioeconomic development. Remarkably, this steady decrease in mortality in non-Qatari females occurred while population growth in this population did not fluctuate in the same magnitude as in non-Qatari males. In non-Qatari males, all-cause ASMR trend decreased significantly between 1998–2010  and reached a plateau thereafter. This significant decrease in mortality appears to have occurred after massive labor migration started. Between 2005–2010, population growth reached a peak at 28% in males. Interestingly, within the same period the decrease in mortality in non-Qatari males was the highest . When population growth in males was below 5% in 1990–1995, 1995–2000, and 2010–2015, AAPCs for the same periods were not significant. The large increase in non-Qatari population within a short span of time could partially explain decreased ASMRs. Of note, ASMR is a weighted average of age-specific rates [In Qatari males and females, all-cause ASMR trends have been steadily decreasing since 1989 . However, mortality in non-Qataris males decreased significantly between 1998–2009 .Between 1991–2014, cause-specific ASMR for cardiovascular and circulatory disease was higher in Qataris than in non-Qataris (both sexes), which resulted in higher ASMRs in Qataris compared to ASMRs in Qatar’s total population Tables . During For cerebrovascular disease, cause-specific ASMR was lower in non-Qataris than in Qataris until 2011 in females and males, which resulted in lower ASMRs in Qatar’s total population compared to ASMRs in Qataris. Mortality in non-Qatari males decreased significantly between 1998–2014 (APC = -12.7%), while in Qataris it decreased significantly between 1991–2001 (APC = -10.8%). In females, mortality was higher in Qataris than in non-Qataris  in 2014. Mortality rates in females were higher than in males .p-value<0.05), while in Qataris (both sexes) and in non-Qatari females, decreased ASMRs were observed a decade earlier .For ischemic heart disease, cause-specific ASMR was lower in non-Qataris than in Qataris (both sexes), which resulted in lower ASMRs in Qatar’s total population compared to ASMRs in Qataris. ASMRs decreased significantly in non-Qatari males since 2001 . In non-Qatari males the trend was constant until 2001 and a significant decrease in mortality was observed thereafter .For hypertensive disease, cause-specific ASMR was lower in non-Qataris than in Qataris (both sexes) between 1990–2014, which resulted in lower ASMRs for Qatar’s total population compared to ASMRs in Qataris. Similar decreasing and significant trends were observed in Qatari females and males and in non-Qatari females . In non-Qataris females, ASMRs were constant.For neoplasms, cause-specific ASMR was lower in non-Qataris than in Qataris (both sexes), which resulted in lower ASMRs in Qatar’s total population compared to ASMRs in Qataris. A significant decrease was observed in non-Qatari males and in Qataris females and males since 1991 , in 2014, ASMRs in non-Qataris and Qataris were similar at 22.5 and 23.7/100,000, respectively. These trends resulted in a constant mortality rate trend for Qatar’s female population.For female breast cancer, cause-specific ASMR was lower in non-Qataris than in Qataris, which resulted in lower ASMRs in Qatar’s total population compared to ASMRs in Qataris. As mortality trends were constant in non-Qataris and significantly declining in Qataris .For prostate cancer, cause-specific ASMR was lower in non-Qataris than in Qataris, which resulted in lower ASMRs in Qatar’s total population compared to ASMRs in Qataris. Mortality in non-Qataris, of which the vast majority is constituted of young people, remained stable. However, in Qataris, mortality trend declined significantly since 2000 . Between 2000–2014, in non-Qatari females and males, mortality trends were constant; except for males between 2005–2010 .For injuries, cause-specific ASMR was lower in non-Qataris than in Qataris (both sexes), which resulted in lower ASMRs in Qatar’s total population compared to ASMRs in Qataris. Qatari males had the highest ASMRs during the study period comparing to Qatari-females and non-Qatari males and females. Mortality decreased significantly in Qatari females and males since 2000 .For all falls, cause-specific ASMR in males was higher in non-Qataris than in Qataris, which resulted in higher ASMRs in Qatar’s total population compared to ASMRs in Qataris. Deaths from falls were recorded for Qatari females only in 2005 . In non-Qatari females, deaths were recorded between 2007 and 2014; and ASMRs  ranged from 0.4 in 2014 and 2.5 in 2010 (modeled trend was constant). In Qatari males, deaths from falls have not been recorded since 2009 . In non-Qataris, mortality decreased significantly in males between 2001–2014 from 5.1 to 2.6/100,000 , while it was constant in non-Qatari males. In 2014, in males, ASMR was 13.4 and 53.8/100,000 in non-Qataris and Qataris, respectively. In females, it was 3.7 and 11.3/100,000 respectively.For transport injuries, cause-specific ASMR was lower in non-Qataris than in Qataris (both sexes), which resulted in lower ASMRs in Qatar’s total population compared to ASMRs in Qataris. Mortality trends decreased significantly in non-Qatari females and in Qatari females and males . As reported elsewhere , 11, numThe healthy migrant effect has been described in other countries such as Australia , FinlandFor injuries, mortality in non-Qatari males and females was lower than in Qatari males during the study period. In 2014, mortality due to falls was 0.4/100,000 in females and 2.6/100,000 in males. Remarkably, mortality due to falls in non-Qatari males decreased significantly suggesting safety improvement in the work environment. Non-Qatari males’ work environment seems to have improved over time. In 2010–2013, yearly fatal occupational rate was 1.6/100,000 in the only designated hospital for major injury treatment in Qatar , 43. ThiThe influx of migrants has enabled Qatar to address the labor shortfall in the country. This migration emphasizes the substantial levels of economic growth observed in the country in the last decades . MortaliOur study demonstrated that while young adult males in Qatar die predominantly from injuries, young adult females die from neoplasms. These identified causes of death are for a large part preventable and should be addressed appropriately to lower premature mortality among young adults in Qatar. In 2013, a law was enacted to ensure the implementation of a mandatory health insurance system of basic health services to all residents of Qatar . As treaRegarding Qatari citizens, the access to free healthcare, housing grants, and subsidized education that accompanied the socioeconomic development of the country  has likeThe strength of our study is that we emphasize demographic specificities in Qatar that should be taken into consideration when developing, implementing, and monitoring public health programs. Policy makers may use the estimated mortality rates and be able to distinguish between nationals (Qataris) and migrants (non-Qataris) when developing strategies to address premature mortality causes. Our analysis is relatively exhaustive unlike previous reports like GBD 2015 , which dThe use of these secondary mortality data has several limitations such as missing data for several years and causes of death. Data validity is also difficult to assess because all data are retrieved from the same source (MDPS) . NeverthQatar’s overall mortality trends appear to be partially attributed to the healthy migrant effect, as migrants have lower mortality rates. Nevertheless, Qatar’s socioeconomic development does also appear to drive mortality decline in both Qataris  and non-Qataris (migrants). Yet, premature mortality remains and might be addressed by scaling-up screening programs and encouraging healthy lifestyle and road safety.S1 FigData source: MDPS’s Census, Population, Housing, and Establishments annual report for the year 2014 .(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.