Avena sativa L.) remain relatively under-researched compared to other small grain species. This study explores the historic context of current elite germplasm, including phenotypic and genetic characterization, with a particular focus on identifying under-utilized areas. A diverse panel of cultivated oat accessions was assembled from the USDA National Small Grains Collection to represent a gene pool relatively unaffected by twentieth century breeding activity and unlikely to have been included in recent molecular studies. The panel was genotyped using an oat iSelect 6K beadchip SNP array. The final dataset included 759 unique individuals and 2,715 polymorphic markers. Some population structure was apparent, with the first three principal components accounting for 38.8% of variation and 73% of individuals belonging to one of three clusters. One cluster with high genetic distinctness appears to have been largely overlooked in twentieth century breeding. Classification and phenotype data provided by the Germplasm Resources Information Network were evaluated for their relationship to population structure. Of the structuring variables evaluated, improvement status (cultivar or landrace) was relatively unimportant, indicating that landraces and cultivars included in the panel were all sampled from a similar underlying population. Instead, lemma color and region of origin showed the strongest explanatory power. An exploratory association mapping study of the panel using a subset of 2,588 mapped markers generated novel indications of genomic regions associated with awn frequency, kernels per spikelet, lemma color, and panicle type. Further results supported previous findings of loci associated with barley yellow dwarf virus tolerance, crown rust (caused by Puccinia coronata f. sp. avenae) resistance, days to anthesis, and growth habit (winter/spring). In addition, two novel loci were identified for crown rust resistance.Population structure and genetic architecture of phenotypic traits in oat ( Avena sativa L., 2n = 6x = 42) has played an important role in the development of agriculture around the world, but received less investment from the plant and agricultural research sectors during the twentieth century than other small grain crops such as wheat and barley (Oat (d barley . The oatd barley .Evidence from existing studies of mid- to late-20th century samples of oat genotypes suggest that cultivated oat populations show high diversity. In a study of 83 North American oat cultivars using restriction fragment length polymorphisms (RFLPs), polymorphism was found to be 54.8% in oat as compared to 5% in wheat and 28% in barley , supportHordeum vulgare L.), genotypes fall into distinct sub-populations based on row number (2 vs. 6), growth habit (winter vs. spring) and geographical origin  representing cultivars collected before 1930, and landraces collected through the 19th and 20th centuries. Genotyping was performed using a SNP array developed for hexaploid oat by A. sativa L. accessions were selected from among the 9,283 available from the NSGC in 2013. The sample was composed of (1) 383 accessions selected from either cultivars or from accessions of uncertain improvement status that had entered the NSGC before 1930; and (2) 617 accessions selected from among all available landraces. Cultivars that entered the NSGC before 1930 are likely to be representative of the same population structure as the landraces, because improved varieties of that era were largely selections from landraces or selections from crosses combining two to four landraces  protocol  with mod2.Genotypes for 4,975 SNPs were acquired using an oat iSelect 6K beadchip array  at the USDA-ARS Genotyping Laboratory at Fargo, ND, USA. SNP genotype calls were made with GenomeStudio v2011.1  with GenCall set at 0.15. In addition, SNP calls were manually inspected and adjusted in GenomeStudio. Multi-allelic and monomorphic SNPs were eliminated, as well as those with poor genotype calls due to weak signal or ambiguous clustering. There were 2,715 SNPs with no more than 5% missing calls and/or heterozygosity, and at least 5% minor allele frequency (MAF). Genotypic data is deposited in the public database T3/oatSingle nucleotide polymorphism data were additionally used to screen for duplicates within the panel. Three hundred and twenty-four lines were identified as duplicates with one or more other lines at a threshold of 99.5% identity. A single line was retained from each set of duplicates based on completeness of genotype data. An additional accession was removed due to unidentified problems in the genotype coding. The final sample had 759 accessions.3 on September 22, 2014 and are representative of the entire NSGC accession rather than the single plants used for genotyping. For that reason, phenotypes recorded in GRIN as a range or as mixed were considered missing data. In all but rare cases, GRIN data are based on unreplicated experiments. Country of origin was used to assign each accession to a region of origin as defined by the United Nations Statistics Division4.Phenotypes were downloaded from the GRINhttp://www.ars-grin.gov/npgs/searchgrin.html. In brief: Awn frequency, hullessness of the threshed grain, amount of plant lodging near maturity, panicle density, panicle type, shattering, and straw breakage at maturity were assessed by visual observation. Beta glucan, lipid, and protein content of the kernel were expressed on a percent dry weight basis. Reaction to BYD virus was evaluated on a 1-9 scale with 1 = resistant and 9 = susceptible. Crown rust (Puccinia coronata) reaction was to a naturally occurring mixture of races in the Saint Paul, MN buckthorn nursery. Reactions rated highly resistant, resistant, moderately resistant to resistant, moderately resistant, moderately resistant to moderately susceptible, moderately susceptible, moderately susceptible to susceptible, and susceptible were converted to a numerical score from 0 to 7 for analysis. Crown rust severity was assessed as the percentage of leaf area affected per plot. Reaction to greenbug (Schizaphis graminus) was assessed as the percent of the resistant check ‘Andrew’. Growth habit was assessed after spring planting in Aberdeen, ID, USA as facultative, spring, winter, or a mix of types. However, we used only those deemed spring or winter for analysis. Days to anthesis was recorded as the Julian calendar date at which 50% of spikes are fully emerged, following spring sowing. Kernels per spikelet and spikelets per panicle were averaged over five panicles. Lemma color was evaluated using a Foss GrainCheckTM 2312 Analyzer . Lemma color was coded based on GC color intensity where 1 < 46.00 (black), 4 = 46.01 to 57.99 (gray), 6 = 58.00 to 71.99 (red), 9 = 72.00 to 82.99 (yellow), and 8 > 83.00 (amber/white). Panicle length was taken as the average distance (in cm) between the lowest node and the tip of the apical spike over five panicles. Plant height was taken as the average distance (in cm) from the ground to the panicle tops. Reaction to smut was recorded as the amount of the combination of covered smut (Ustilago kolleri) and loose smut (U. avanae) expressed as a percent of the susceptible check. Straw color was recorded as 1 = black, 2 = blue, 3 = brown, 5 = purple, 7 = tan, 8 = white/amber, and 9 = yellow. Test weight of grain was reported in pounds per bushel. Yield was recorded as the weight of harvested grain in grams per unreplicated 2.44 m row.Detailed descriptions of phenotyping methods are available at Principal component analysis (PCA) was performed in TASSEL v.4.0 . PrincipK value (number of population clusters) were run for K = 1 to 12. Burn-in was set to 10,000 and Monte-Carlo Markov Chain replications (MCMC) to 25,000 after burn-in. Values of L(K) (log posterior probability of the data) returned by STRUCTURE were averaged across simulations for each K value. Following the method of L(K) between values of K (ΔK) was created. A further run with burn-in = 100,000 and 100,000 MCMC replications was performed to assign individuals to population clusters using the value of K inferred from the initial run. A threshold of 80% genetic membership coefficient was used to assign genotypes to a specific cluster, below which they were designated ‘admixed’.STRUCTURE software version 2.3.4  was usedUsing the relationship matrix function in JMP Genomics, distance-based hierarchical cluster analysis was done by first generating a similarity matrix based on allele sharing for each accession pair using the subset of SNPs without missing genotype calls. Accessions were then grouped by the Fast Ward hierarchical clustering procedure.Distribution of phenotypic or origin categories across inferred population clusters was explored by calculating expected distribution based on random allocation of category members to clusters, and calculating over- or underrepresentation based on deviation from expected values as a proportion of group membership. Observations were generally noted if they exceeded 15% deviation from expected values. Statistical significance of results was tested by the chi-squared test. For evaluation of patterns in year of collection, accessions were grouped by decade of collection to avoid excessively small cell sizes in the analysis. Because classification as ‘fall sown’ vs. ‘spring sown’ is not undertaken in GRIN, classification as ‘red’ vs. ‘common’ type and winter vs. spring growth habit were evaluated as possible substitutes.N > 80 accessions in the panel.For the majority of GRIN phenotypes, observations for each accession were taken in a single study environment with no accessions common to multiple study/environments which could be used to estimate environmental effects. Because of this, association analyses were performed within study environments and only for those with Single nucleotide polymorphism locations were taken as those on the oat consensus map version 3.1 reported by p ≤ 1.93 × 10-5, calculated by applying the Bonferroni correction method with an experiment-wise alpha level set at 0.05.Genotype-phenotype association was evaluated using a mixed linear model (MLM) procedure in TASSEL v4  under thA. sativa collection, the panel compiled for this study had proportionally fewer cultivars and accessions of uncertain improvement status compared with landraces. This distribution is undoubtedly due to the fact that we limited our selection of cultivars to those entered before 1930. Within the landraces, the present sample maintains the collection year and region of origin distributions of the NSGC  showed a rapid reduction in ΔK, normally regarded as a signal that the true value of K has been reached, between K = 3 and 4. A further run of STRUCTURE was used to assign accessions in the panel to three population clusters (Table 1). Seventy-three percent of accessions exceeded the 80% membership threshold and could be assigned to a specific cluster, while 27% were considered admixed. Cluster 1 was more divergent from 2 or 3 than they were from each other, based on indicators from both STRUCTURE  and hierarchical clustering . Cluster 2 contained the fewest members but showed the highest within-group gene diversity of all clusters (Table 1). Overlap between cluster assignments based on PCA, hierarchical clustering, and model-based analyses confirmed that all detected the same population structure. STRUCTURE-assigned groupings were used for further evaluation of origin and phenotypic trait distribution across population clusters.The first three principal components (PC) accounted for 23.6, 11.8, and 3.4% of marker variation, respectively . The first five PC together accounted for 43.3% of genetic variation among accessions. A plot of the eigenvalues of the first 25 PC suggested that the first three PC account for most of the population structure in this panel (not shown). Similar results were obtained from the model-based analysis where the plot of Table 2). Assignment to the STRUCTURE groupings accounted for the largest proportion of among-group genetic variance. Lemma color and region of origin groups showed some importance as explanatory variables, while growth habit and classification as ‘red’ or ‘common’ oat were far less important. Improvement status groups accounted for only 2.5% of variance, suggesting that that landraces, unimproved material, and cultivars are all drawn from the same underlying population structure.AMOVA was used to compare a range of variables for their power to explain genetic variability in the panel (p < 0.01).Improvement status, region of origin (collection site), growth habit , lemma color, and ‘red’ vs. ‘common’ classification were explored for their association with STRUCTURE population clusters. The chi-squared test showed non-random distributions for all traits studied (Table 3); cluster 2 as widely distributed across Central Asia and Europe; and cluster 3 as predominantly European and North American. North American accessions, which account for 18.8% of panel members, are overrepresented in the admixed group and underrepresented in cluster 1. Cluster 1 was almost entirely composed of landraces (Table 4). ‘Spring’ growth habit was predominant across the whole panel (78% of rated entries), but those accessions designated ‘winter’ appeared highly disproportionately in cluster 1, somewhat disproportionately in cluster 2, and were underrepresented in cluster 3 (Table 4).Cluster 1 was characterized as coming predominantly from Western Asia , Southern Europe and Northern Africa (Table 4). Black oats were in excess in the admixed group, while gray lemma color was in excess in clusters 1 and 2 and red color in cluster 1. There was imperfect correspondence between accessions with red lemma color and those classified as ‘red’ type oats: 61% of accessions with red lemma color were classified as ‘common’ oat, and 38% of all oats classified as ‘red’ type had yellow, gray or black lemma color. A PCo plot colored by the ‘red’/‘common’ classification  suggested that ‘red’ types cover a similar extent of genetic space to that covered by ‘common’ accessions, but are concentrated in cluster 1 (38% overrepresentation at p < 0.01). Cluster 1 consists of 59% ‘red’ oats, and 54% of all accessions classified as ‘red’ type belong to this cluster.Evaluation of lemma color showed that yellow-hulled oats were disproportionately likely to come from cluster 3, which was also less likely to be a source of black, gray, or red lemma colors .Cluster 1 showed substantially higher mean kernel weight than other clusters (Table 6). Supplementary Figures Sample size and phenotypic distributions (mean and standard deviation) of traits used in association analyses are presented in Supplementary Tables Table 6; Supplementary Figure p-value in Urbana 85 (p = 0.036), providing a true replicate for this effect.A cluster of SNPs at 70.2 to 70.5 cM on Mrg17 was associated with reaction to BYDV evaluated in Urbana 84, but not in Urbana 85  of this marker-trait association was observed in Aberdeenr 84 (not shown). The same marker was also associated at p < 1.0 × 10-4 with crown rust reaction and severity in Saint Paul 97, and with awn frequency in Aberdeen 83.A QTN for days to anthesis (heading date/flowering time) was detected on Mrg02 at 60.4 cM in Aberdeen 83 , whereas those carrying the minor allele were more likely to be either red (31.6%) or black (21.1%).Studies of the global gene pool of cultivated oat have generally reported weak structure. PC1-5 accounted for 23.8% of genetic variation in the 635-member CORE panel of elite cultivars , and 22.The lack of correspondence between these subgroups and classification as ‘landrace’ or ‘cultivar’ (explaining only 2.5% of genetic variation in AMOVA) reflects the early historical era during which cultivars in the panel were collected. Cultivars in the present study all entered the NSGC prior to 1930. In the late nineteenth and early twentieth centuries, oat cultivars tended to be selections from landraces rather than artificial crosses, and breeding programs with highly managed germplasm pools did not yet exist.Table 5), which is both an important center of diversification for Avena sp and a region where they are less important as a cultivated crop (Lemma color was strongly associated with population structure as quantified by AMOVA (13.8%). Indications from earlier quantitative work e.g., . One posted crop . AccessiRegion of origin (collection site) accounted for 13.1% of genetic variation by AMOVA, a similar proportion to that captured by lemma color. Its importance to population structure in the present study echoes the findings of The population structure of the germplasm panel used in our study clearly shows a genetic cluster that has largely been overlooked in 20th century breeding. Cluster 1 was characterized by high genetic distinctness and relatively low internal diversity, with a high proportion of red and winter oats. A similar cluster was identified in a previous survey of global oat germplasm by r2> 0.10 was observed within linkage groups at an average distance between markers of 0.44 cM. The same value was estimated as 2.5 cM by The power and resolution of GWAS is influenced by LD between markers in the population studied, and every population is associated with its own unique pattern of LD. In a worldwide panel of 635 elite breeding lines, The same authors suggested in their study that a minimum of one marker every cM be used for GWAS in oat. The use of historical phenotypic data in these analyses resulted in what can be considered several small studies of genotype-phenotype association, each with an independent sample evaluated in a single environment  and without replications. Small sample size, lack of replication within or across environments and the relatively small number of markers available represent limitations on the power of the present study to reliably detect small to moderate SNP effects on phenotype, so we suggest that results should be interpreted as exploratory, with the primary purpose of highlighting genomic regions of interest for future research. For these exploratory GWAS, we chose to apply the same MLM approach to all genotype-phenotype analyses. It is likely that a more nuanced approach in future efforts would improve statistical power to detect QTL for some phenotypes, especially in the case of a skewed distribution or a genetic architecture characterized by rare variants and moderate effect sizes . Given tFigure 4 (Mrg17 and 20) and Supplementary Figures Association mapping analyses conducted for the present study address several traits which have not been part of recent molecular work in oat and thus represent an initial attempt to discover their underlying genetics. The inclusion of a broad range of traits presents opportunities to look at relationships between them. The recently completed oat consensus map also permits the examination of our findings together with previously identified marker-trait associations. A visualization of the annotated oat genome in Figure 4). The region appears to be homologous with one carrying markers for a major BYD tolerance locus identified in separate oat populations by Ryd3 is a major gene for BYD tolerance in barley which has been mapped to a genetic interval corresponding to a segment of rice chromosome Os02  and Pc91, respectively . No candidate genes could be found for seedling resistance markers on Mrg23 and Mrg01, though they could exist among the many Pc genes yet to be mapped.The present study identified five SNPs associated with oat seedling resistance on Mrg01, Mrg08, Mrg20, Mrg23 and Mrg28. Candidate genes for SNPs on Mrg08 and Mrg28 are ectively , 2015. TFor protection of oats against crown rust, oat breeders have tended to turn to race specific seedling resistance conferred by single genes such as those described above; but the crown rust pathogen is highly variable and has been shown to quickly overcome such resistance . Recent Pc38 which situate it at approximately 70 cM on Mrg02  for crown rust reaction and severity and one marker significant for days to anthesis (GMI_ES03_c7453_413). A marker for heading date of unvernalized plants identified by Vrn1 by Pc48. One explanation for such findings is that developmental stage of the plant influences its susceptibility to the crown rust pathogen.Up to three loci have been observed to control lemma color, depending upon the specific cross, with interactions between loci including epistatic dominance  and complementarity  . Furtherp = 0.002) was observed for marker BA_grs_c8269_158 on Mrg17 at 34 cM, just distal to the SNPs associated with awn frequency on that linkage group.Awn formation is associated with lemma color in certain genetic backgrounds . We wereper se (rate of plant development), in particular since the vernalization requirement of oat is often facultative and weak . This region contains heading date QTL regions mapped in the KO and OT populations  in Aberdeen 83 co-locates with a second marginal association with growth habit in Aberdeen 96 and days to anthesis in Aberdeen 84  with heading date response to vernalization observed in the Kanota × Ogle population and with heading date after early planting in the field observed in the Ogle × TAM O-301 population  can be viewed with more confidence. However, we found no evidence of association with growth habit (or days to anthesis) on linkage groups Mrg09, Mrg12, or Mrg20, all of which have been reported to carry QTL mapped by both linkage and association and which carry candidate genes mapped by sequence homeology .Numerous regions of the oat genome have been implicated in the control of flowering time, vernalization response, and photoperiod response (summarized in Significant associations were not identified in the present study for groat beta glucan, groat lipid, groat protein, plant height, test weight, lodging, yield, panicle length and density, smut reaction, straw breakage, shattering, greenbug reaction, and bundle weight. Previous studies have mapped QTL for groat beta glucan , groat lCultivated oat is a widely adapted cereal with greater ecological range than either wheat or barley . High moThe present study assembled a panel of historic and unimproved oat accessions from the NSGC with the goal of sampling germplasm that predates the influence of major breeding advances in the 20th century as a complement to similarly diverse but more recent panels. Population structure in this panel appeared to be stronger than that identified in previous studies. Primary explanatory variables were region of origin and lemma color. While ‘red’/‘common’ type or winter/spring growth habit classifications were relatively uninformative, available evidence was insufficient to establish whether they could be considered equivalent to the ‘fall sown’/‘spring sown’ classification found to account for structure in more recent oat panels.Most accessions in the panel could be assigned to one of three population clusters. One of these clusters was more genetically distant from the other two and contained a disproportionately high concentration of accessions classified as ‘red’ type, winter, with red or gray lemmas and/or originating from Western Asia. This cluster appears to have been largely overlooked during twentieth century breeding and may be a valuable source of germplasm for future breeding work, particularly given its high average kernel weight.Ryd3. Six loci were associated with crown rust reaction, most of which appear to be linked with previously reported genes. Loci on Mrg01 and Mrg23 are reported here for the first time.Association mapping analyses conducted as part of the present study generated the first evidence of chromosomal regions controlling awn frequency, lemma color, kernels per spikelet and panicle type. Other evidence of association generally supported indications from previous studies. A single locus was associated with tolerance to BYD and may be orthologous to barley gene per se. At the same time, genetic relationships between pairs of traits, such as plant height and lodging or yield and heading date, are imperfectly understood and will require well-designed experiments to resolve. More thorough phenotyping of this nature could greatly strengthen characterization of oat germplasm and explanations of population genetic diversity.For future work, findings of the present study suggest the value of a more detailed approach to phenotyping and classification in cultivated oat. Key examples are the measurement of heat tolerance and cold tolerance, as well as the use experimental designs which separate tests of vernalization requirement, photoperiod response and flowering time KEK initiated and organized the study; HB provided germplasm and phenotype information; SC performed genotyping work; LW, KEK, and JMB performed data analyses; LW drafted the manuscript, and KEK, JMB, and BAY contributed material; all authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Previous studies in rabbits identified an array of extrastriate cortical areas anatomically connected with V1 but did not describe their internal topography. To address this issue, we injected multiple anatomical tracers into different regions in V1 of the same animal and analyzed the topography of resulting extrastriate labeled fields with reference to the patterns of callosal connections and myeloarchitecture revealed in tangential sections of the flattened cortex. Our results extend previous studies and provide further evidence that rabbit extrastriate areas resemble the visual areas in rats and mice not only in their general location with respect to V1 but also in their internal topography. Moreover, extrastriate areas in the rabbit maintain a constant relationship with myeloarchitectonic borders and features of the callosal pattern. These findings highlight the rabbit as an alternative model to rats and mice for advancing our understanding of cortical visual processing in mammals, especially for projects benefiting from a larger brain. An important goal of visual system studies in animals is to understand vision in humans. In past decades, emphasis has been placed on studying carnivores and nonhuman primates based on the belief that advanced species resemble humans in both behavior and brain organization more closely than less advanced species, such as rodents, whose visual system has been widely assumed to be much simpler by comparison. However, numerous studies in rats and mice have convincingly shown that the occipital cortex surrounding primary visual cortex  is significantly more elaborate than previously thought, consisting of about a dozen of interconnected, topographically organized extrastriate visual areas . This knHowever, the small size of the brains in rats and especially mice presents some challenges, such as greater difficulty in locating and recording from small cortical areas. Experiments benefiting from, or requiring larger brains, such as studies using stimulating/recording microelectrode arrays to explore the potential for chronic recordings in visual cortex , or for Surgery was performed in 5 albino and 5 adult Dutch belted rabbits (weighing approximately 2000–2500 g) anesthetized with ketamine hydrochloride  and xylazine hydrochloride , supplemented with atropine sulfate (0.05 mg/kg sc). Procedures followed protocols approved by the Institutional Animal Care and Use Committees.μL of a solution of horseradish peroxidase  were injected into about 50–60 sites across occipital cortex in the left hemisphere. To reveal striate-extrastriate connections, small volumes (0.02–0.1 μL) of several additional tracers were injected at different loci in striate cortex of the right hemisphere . These tracers included the anterograde tracer 3H-proline  and up to three retrogradely transported fluorescent tracers . The approximate area of effective tracer uptake for restricted injections was estimated as described previously [μm tip diameter) using brief pressure pulses.To reveal the distribution of callosal connections in the right hemisphere, total volumes of about 9.0–10.0 eviously . All traμm thick sections) as described previously [μm thick coronal sections. The transport of 3H-proline was revealed in sections processed for autoradiography [After 3–5-day survival, animals were deeply anesthetized with pentobarbital sodium (100 mg/kg ip) and perfused through the heart with 0.9% saline followed by 4% paraformaldehyde in 0.1 M phosphate buffer (pH 7.4). The right cortical mantle was resected, flattened between glass slides, and sectioned tangentially , digitized images of anatomical tracers and myelin labeling patterns from the same animal were carefully aligned with each other using the border of V1, the edges of the sections, blood vessels, and other fiducial marks. Cells labeled by the injections of RB, GB, and FB were represented by red, green, and blue dots, respectively, and overall labeling patterns were reconstructed from 3-4 sections. β [Heavily myelinated areas are observed in occipital, temporal, and parietal regions .  Figureβ  was not β .The patterns of callosal connections were revealed in albino Figures  and DutcIn extrastriate cortex callosal connections formed patches and bands, and in some cases callosal bands partially or completely encircled areas devoid of callosal connections in lateral extrastriate cortex . The appn = 5). Tracer injections into V1 were placed in regions representing upper and lower visual fields, as well as nasal and temporal fields  maps along the same direction in LM but in the reverse direction in areas AL and PL. The anteroposterior map in PL appears to reverse again in area P.The RB-labeled field in LM extends further laterally at both its anterior and posterior ends forming two tongues. The posterior tongue is long, extending into areas Te2.1 and Te2.2  we revealed the projections from an injection of tritiated proline placed at the medial border of posterior V1, in a region roughly similar to the FB injection in We confirmed studies showing that callosal connections form a band that straddles the lateral border of V1 , 49. OurThe callosal band at the V1/Oc3.1 border often had a beaded appearance in both albino and Dutch belted rabbits. The presence of callosal patches along this band is in agreement with previous reports in rabbits  and squiRelative to the width of V1, the callosal zone in V1 is narrower in rabbits than in rats , 58. A pOur results extend previous studies and provide further evidence that extrastriate areas identified anatomically in the rabbit , 37 reseIn rats  and miceIn agreement with Montero , we obseIn addition to the first tier of areas located immediately adjacent to the lateral border of V1, we identified a second tier of smaller areas. In one of these, area LI, the mediolateral topography was a mirror image of that in LM, as in rats , 11, 16 The densely myelinated area we observed in Te3 may correspond to a heavily myelinated area, called TP , described in approximately this region in the squirrel , 68 and We did not observe projections anterior to V1 that could correspond to area A (anterior) in rats  and miceIn addition to areas V1 and V2, a previous physiological study  describeOur study provides further information about the location and topography of extrastriate areas connected with V1 in the rabbit and relates these areas to the patterns of callosal connections and myeloarchitecture. Our results should facilitate the interpretation of additional mapping and hodological data obtained in the rabbit with electrophysiological and other techniques and contribute toward comparative studies of the organization of visual cortex in mammals. In view of the similarity that appears to exist between rabbits, rats, and mice, the rabbit offers an alternative model for further studies of the “rodent” visual cortical plan, especially for projects benefiting from a larger brain.


Iron (Fe) deficiency chlorosis (IDC) in soybean results in severe yield losses. Cultivar selection is the most commonly used strategy to avoid IDC but there is a clear interaction between genotype and the environment; therefore, the search for quick and reliable tools to control this nutrient deficiency is essential. Several studies showed that relative humidity (RH) may influence the long distance transport of mineral elements and the nutrient status of plants. Thus, we decided to analyze the response of an “Fe-efficient” (EF) and an “Fe-inefficient” (INF) soybean accession grown under Fe-sufficient and deficient conditions under low (60%) and high (90%) RH, evaluating morphological, and physiological parameters. Furthermore, the mineral content of different plant organs was analyzed. Our results showed beneficial effects of high RH in alleviating IDC symptoms as seen by increased SPAD values, higher plant dry weight (DW), increased plant height, root length, and leaf area. This positive effect of RH in reducing IDC symptoms was more pronounced in the EF accession. Also, Fe content in the different plant organs of the EF accession grown under deficient conditions increased with RH. The lower partitioning of Fe to roots and stems of the EF accessions relative to dry matter also supported our hypothesis, suggesting a greater capacity of this accession in Fe translocation to the aerial parts under Fe deficient conditions, when grown under high RH. Humans and plants need essential micronutrients for the proper functioning of cellular processes  is a common symptom caused by lack of available Fe, occurring worldwide. It is characterized by a significant decrease in chlorophyll leaf content  is one of the most highly produced legumes worldwide  can indirectly provide valuable information about nutrient translocation in plants. It is known that the reduced transpiration due to increased RH  has an important role on plant nutritional status. It is known that plants exposed to high RH might show increased growth due to higher stomatal opening, leading to increased uptake of COCitrus aurantium L., Basiouny and Biggs  and Fe-deficient (DEF) conditions, to low (60%) and high (90%) RH. Plants were scored based on the degree of leaf chlorosis (SPAD measurements) and several morphological and physiological parameters such as total plant DW, plant height, root length, shoot DW, root:shoot ratio, and leaf area were measured. We also analyzed the mineral content on the different plant organs  and calculated the partition quotient (PQ), to evaluate the effect of high RH in the flow of several minerals  involved in plant growth and the role of RH on mineral distribution. Ultimately, we were able to relate the degree of plant IDC symptoms with its nutritional status, as affected by RH.G. max accessions with differential IDC response were obtained from the USDA (U. S. Department of Agriculture) germplasm collection via GRIN (Germplasm Resources Information Network) (http://www.ars-grin.gov/): an EF accession - PI 360952, “Amurskaja 310” and an INF accession - PI 407707, “Chuen sien No. 1.” These accessions have contrasting efficiencies in Fe absorption based on the study of Vasconcelos and Grusak 2; 0.3 mM MgSO4.7H2O; 0.2 mM NH4H2PO4; 25 μM CaCl2; 25 μM H3BO3; 0.5 μM MnSO4; 2 μM ZnSO4.H2O; 0.5 μM CuSO4.H2O; 0.5 μM MoO3; 0.1 μM NiSO4. All nutrients were buffered with 1 mM MES  (pH 5.5). The solutions were supplemented with 5 μM Fe(III)-EDDHA  for 7 days followed by 0 μM for an additional 7 days (DEF conditions) or with 20 μM for 14 days (SUF conditions), the latter being replaced every 2 days.Two d Grusak . Plants Leaf chlorophyll content was assessed for evaluation of plant tolerance or susceptibility to Fe deficiency chlorosis. A portable SPAD 502-Plus Chlorophyll Meter  was used for estimating the chlorophyll concentration , in order to evaluate the impact of Fe deficiency and RH on plant-atmosphere water exchange. Three gTo study the effect of RH on plant growth, a series of morphological traits were evaluated. Thus, five plant parts were discerned: roots, stems, unifoliate and trifoliate leaves. After drying tissues at 70°C for 2 days, DW was recorded and the root:plant ratio was calculated as the ratio between the DW of roots and the DW of the whole plant. Plant height and root length were also measured. An AM300 Portable Leaf Area Meter  was used for determining total leaf area. Five plants per accession were used to study morphological parameters.G. max accessions (EF - PI 360952 and INF - PI 407707) were mixed with five mL of 65% HNO3 in a Teflon reaction vessel and heated in a SpeedwaveTM MWS-3+  microwave system. Digestion procedure was conducted in five steps: 1-130°C/10 min, 2-160°C/15 min, 3-170°C/12 min, 4-100°C/7 min, 5-100°C/3 min. The resulting clear solutions of the digestion procedure were then brought to 20 mL with ultrapure water for further analysis. A bulked sample of five plants per accession was used for digestion. Nutrient content was analyzed in the plant organs described above by ICP-OES Optima 7000 DV . All analysis was done in triplicate.Two hundred mg of the different dried plant organs  of the two G. max plants grown under DEF conditions, changes in each tissue's content were normalized to changes in each tissue's weight, relative to the whole plant. The DW of each organ was calculated as a percentage of total plant DW at each RH, and mineral content of each organ was calculated as a percentage of total plant mineral content at each RH. Using these values, the normalized partitioning of each mineral within the plant was calculated by dividing each organ's percentage mineral content by its percentage DW, and multiplying by 100, which we refer to as the partition quotient, as described by Waters and Grusak . Statistical significance was considered at P < 0.05.Significant differences between treatments and cultivars were determined using the unpaired Student's The impact of Fe deficiency was more pronounced in plants of the EF accession grown at 60% RH which developed the typical IDC symptoms: stunted growth and a decreasing chlorophyll concentration trend  relative to plants grown under high RH Figures , 2. TherIn the EF plants grown under Fe deficient conditions, we found that the increase in RH resulted in significantly increased plant height (25%), root length (33%), plant DW (42%), and leaf area (39%) but it had no significant effect on the root:shoot ratio Table . RegardiConcerning the morphological changes induced by Fe deficiency, we did not find significant differences for plant height and root:shoot ratio between the two studied soybean accessions, in all treatments Table  statist.Dry weight of INF plants grown under Fe sufficient conditions was significantly higher when plants were grown under Fe sufficiency Table . The leas with RH regardless of Fe status, but it was only statistically significant for the EF accession grown under sufficient conditions . For the INF accession, the lack of Fe significantly decreased (52%) the leaf gs at low RH. Also, gs of INF plants grown under Fe sufficient conditions, at both RH conditions, was significantly higher comparatively to that obtained by the EF plants .For both accessions, there was a tendency for the increase of gs Figure . In the P > 0.05) the Fe content in roots of plants grown under Fe deficiency  comparatively to plants grown at low RH Figure . HoweverThe beneficial effect that high RH produced in suppressing IDC symptoms of the EF accession could also be seen through the other analyzed morphological parameters. High RH exposure led to an increased plant height, root length, plant DW, and leaf area Table  grown unOn the other hand, the root:shoot ratio of plants of the INF accession grown under Fe deficiency was significantly higher when RH increased because the INF accession invested on the production of higher root biomass, the organs responsible for the uptake of Fe, to overcome Fe deficiency. We can conclude that the different ability of the two soybean accessions for Fe absorption is linked to root length, plant DW, and leaf area but not to plant height, as Elmstrom and Howard  found. IBegonia × hiemalis “Schwabenland Red” grown at high RH were significantly higher than those found in plants grown at low RH; the increase in leaf size as a result of exposure to high RH have been reported as well on lettuce, wheat, sugar beet, cotton, and numerous greenhouse plants by Hoffman and Rawlins (Our results confirm that plant growth is affected by RH, as suggested before. Gislerød and Mortensen  found th Rawlins , Ford an Rawlins , Tibbitt Rawlins , and Mor Rawlins ; high RH Rawlins .Concerning the Fe content—our main focus—in all studied plant organs, it significantly decreased when plants were grown under Fe limiting conditions in both accessions, regardless of RH Figures , as expeThe calculation of PQ allowed us to better understand the effect of RH in the mineral distribution of plants subjected to Fe limitation. The low PQ values obtained in roots and stems and high in unifoliate and trifoliate leaves of the EF accession grown at high RH for almost every studied mineral Figure  are indiOn the contrary, the low PQ values found in roots of both accessions for almost every mineral are associated with an increased remobilization of nutrients to the aerial parts, regardless of RH. The highest PQ values found in stems of EF accession may be related to the fact that they are responsible for the transport of minerals between the below ground organs to the aerial parts, and so, it is expected that here the mineral content is low, also shown by the results of the Fe content Figure . PQ valus by the Fe deficient IN plants (Figure s caused by Fe deficiency, which could partly explain the increased resistance to IDC.These differences in the PQ values between treatments can also be associated with the mobility of minerals in the xylem because of the impact of RH on the transpiration rates. Fe is transported to the shoot through the transpiration stream, circulating in the xylem as ferric-citrate complexes (Rellán-Álvarez et al., s Figure  could beFe must also be transported through the phloem, because the transpiration flow in the xylem vessels is inefficient in apexes, seeds, and root tips (Kim and Guerinot, Finally, all the performed analysis allowed us to conclude, through morphological and physiological parameters, that effectively, high RH affected plant growth and development. Furthermore, high RH alleviated IDC symptoms in Fe efficient plants grown under deficient conditions. This mitigation could be seen through increased SPAD values Figure , plant hMariana Roriz carried out the sample preparation and analysis, mineral quantification by ICP-OES and drafted the manuscript; Susana M. P. Carvalho helped conceive the study and its design, and participated in the critical review of the manuscript; Marta W. Vasconcelos conceived the study, its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The quality of diabetes care remains suboptimal according to numerous studies assessing the achievement of quality indicators for diabetes care in various healthcare settings. We report about global and specific quality indicators for diabetes care and their association to glycemic control at the population level in two national health surveys in Mexico.We conducted a cross-sectional analysis of the 2006 and 2012 National Health Surveys in Mexico. We examined quality of care for 2,965 and 4,483 adults (≥ 20 years) with diagnosed type 2 diabetes using fourteen simple and two composite indicators derived from self-reported information. In a subsample for both surveys, glycated hemoglobin (HbA1c) was measured at the time of the interview. We obtained survey weight-adjusted estimators using multiple regression models (logistic and linear) with combined data files, including survey year as covariate to assess change.Global quality of care in 2012 was 40.8%, with a relative improvement of 11.7% between 2006 and 2012. Detections of cardiovascular disease risk factors (dyslipidemia and hypertension) were the indicators with the highest improvement, while non-pharmaceutical treatment and diabetic foot exams showed minor changes. We found a significant association between the quality of the process of diabetes care and glycemic control . Age more than 65 years old, the type of health subsystem, gender , and high socio-economic status were also significantly associated to glycemic control.Quality diabetes care and glycemic control improved and are significantly associated. However, according to international standards, the current situation remains suboptimal. A more holistic approach is needed, with an emphasis on improving quality in outpatient care. This composite indicator was estimated for: (i) all 14 indicators ; (ii) the 10 general indicators ; and (iii) the four indicators that apply only to those with an additional cardiovascular disease risk factor .To summarize overall quality of care we use two composite indicators –28: “perGlycemic control was defined by individual HbA1c targets based on age and presence of complications : for those younger than 45 years without complications ((≤ 6.5%) [≤ 47.5 mmol/mol]), and with complications ((≤ 7.0%) [≤ 53 mmol/mol]); for those aged 45 to 64 years without complications ((≤ 7.0) [≤ 53 mmol/mol]), and with complications ((≤ 8.0%) [≤ 63.9 mmol/mol]); and for those aged 65 or more years without complications ((≤ 7.5%) [≤ 58.5 mmol/mol]), and with complications ((≤ 8.0%) [≤ 63.9 mmol/mol]) –18, 27 bSocioeconomic-status (SES) was measured using a previously validated index , which whttp://ensanut.insp.mx/Available Data in: Access to the database (Bases de datos y documentación) held by National Public Health Institute, Center for Evaluation and Survey, ENSANUT, requires the completion of a free user registration (Formulario de Registro). One time registration will provide a username and password via e-mail in order to access all relevant data.http://ensanut.insp.mx/forma_registro.php#.VZLNK_l_OkoLink to Registration (Formulario de registro): relative improvement) was calculated as follows: (absolute improvement/possible room for improvement)x100 = [absolute improvement/(100-percentage of compliance in 2006)]x100 x100 . For thet distribution and by computing 95% confidence intervals (CI), .To assess adjusted changes between the two surveys and the influence of quality process criteria on glycemic control, we used a combined 2006 and 2012 data file creating new weights using jackknife replication method, with R = 80 replicate weights for each survey year, given that each ENSANUT samples are drawn independently and with different weights. In this combined file, ENSANUT 2006 is year 1 and ENSANUT 2012 year 2. The analysis followed the methodology described by Lee S, et al. , taking  and SES by quintile . To test if the composite global quality of process indicator was associated to glycemic control, we restricted the data set to the eligible group, using the subpopulation estimation for survey data (the “svy” command with “subpop” option) for observations with HbA1c measurements. In the multiple linear regression model HbA1c is expressed as percentage; we analyzed the adjusted association with the percentage of global quality care. In the logistic regression model HbA1c is expressed as achievement of individualized target based on age and presence of complications  and we calculated adjusted Odds ratios (OR) with 95% CI to identify significant associations.To assess the relationship between quality of care and glycemic control, we used regression models (multiple linear and logistic), where glycemic control was the dependent variable, and the quality of care indicators  as the independent variables. We included in the models the following adjusting covariates: survey year (1 or 2), gender , age (<45 years = reference), time since diagnosis of diabetes (≤10 years = reference), presence of diabetes-related complications, presence of cardiovascular disease risk factors, type of health subsystem .The National Surveys showed a significant increase in the prevalence of people who knew they suffered from Type 2 diabetes (7.0% in 2006 to 9.1% in 2012); the estimated change between years was 2.1% (95% CI 1.5–2.7%), (data not shown in table).Most of the process of care indicators showed improvement, although uneven and not always significant, with several indicators worsening . SalientAmong patients who reported hypertension or dyslipidemia in addition to diabetes , the incOverall quality estimated by composite indicators remained below 50% in 2012, yet showed a significant increase in relation to the 2006 estimates . OverallThe global quality of care indicator including all 14 indicators, changed 7.7 percentage points (from 33.1% in 2006 to 40.8% in 2012). This change remained significant after adjusting for age, gender, time of diagnosis, presence of complications due to diabetes, presence of cardiovascular disease risk factors, type of health subsystem, and SES .Both regression models, logistic and linear, revealed a significant association between the global quality of care composite indicator and glycemic control .Seguro Popular affiliates as compared to other social security schemes. However an inverse relationship occurs when comparing females to males. Glycemic control is also significantly better in 2012 as compared to 2006 . The model is adjusted by time since diagnosis, presence of complications due to diabetes, and presence of CV risk factors.Adjusted OR in the logistic model for global quality in relation to glycemic control is 2.53 (95%CI: 1.63–3.94). The same significant association but with higher OR holds for the older age categories compared to the youngest category, higher SES compared to lower, and private and The linear regression model, with glycemic control expressed as % of HbA1c and global quality as a percentage of composite indicator compliance, shows the same consistent results: a significant association between global quality and level of HbA1c , indicating that 1 percentage point increase in global quality of care is associated to a decrease of 0.95 to 1.6 percentage points in HbA1C, adjusted by all the other considered variables.Logistic regression, included in the model for all simple quality care indicators as independent variables (data not shown in table), shows a significant association between the use of health services  and glycemic control, and also better in those tested for HbA1c at least twice a year . In addition, when compared to those receiving no drug treatment, the frequency of insulin use was significantly higher in uncontrolled patients treated either with insulin only  or with insulin combined with oral hypoglycemic agents . Other factors associated to glycemic control were detection of hypertension (OR: 0.86 95% CI: 0.74–0.99), detection of dyslipidemia , and diet and exercise plan (OR: 0.31 95% CI: 0.19–0.52).The results of this study show that despite the progress that Mexico has made in diabetes care, there is still considerable room for improvement. Global quality is still below 50%, and many of the relevant specific indicators have not improved significantly over the last six years. There is controversy regarding some indicators such as the appropriate number of physician visits and the benefit of insulin compared with oral hypoglycemic agents . HoweverAmong our study results, a significant increase in the prevalence of diabetes and its complications, poor compliance with prevention actions, and enhanced pharmacological treatment all suggest a reactive attitude by the health care system in general. This stresses the need to implement a comprehensive care model including all aspects of prevention, both primary and secondary, along with a more proactive attitude by healthcare providers.Seguro Popular. However, positive results from these efforts at the population level are still scarce, which may be partially related to the deficient quality of the actual care provided. In 2012, more than 85,000 people died in Mexico from diabetes-related causes [Mexico has implemented specific programs that seek better and more holistic care for patients with diabetes –36, in ad causes , with anInternational studies show that good quality of diabetes care is difficult to achieve –42. In tInsulin use is an important and controversial issue. It varies greatly among countries (more in developed than in developing countries) and with patient age . In a comparison of 65 studies, the rate of insulin use among patients in Mexico was ranked among the lowest at <15% . In thisCompliance with the number of physician visits and HbA1c testing were associated with glycemic control. Evidence regarding the regularity with which Type 2 diabetes patients need a medical review is still scarce, but at least one visit every three months is generally recommended ,45. FurtGlycemic control is the best indicator of the effectiveness of diabetes care, and is associated with fewer cardiovascular and renal complications , 47. SomAggressive treatment targets for glycemia (such as HbA1c level <6.0% and <6.5%) in large randomized, controlled trials were associated with harmful outcomes , increasSome limitations of this study should be mentioned, such the biases inherent in data obtained through surveys, residual confounding through unmeasured variables, the observational and transverse nature of its design, and possible differences among survey formats. However, the validity of the information obtained from patients in relation to other data sources such as medical records has previously been demonstrated in numerous studies , 53. WitOur study offers new insight into quality improvement strategies stratified by groups of patients with poor glycemic control and who may benefit from targeted interventions, in particular, younger adults. Tricco et al.  confirmeHowever, few intervention studies have focused on addressing challenges faced by younger adult patients with Type 2 diabetes. Further research is needed to determine what interventions may be appropriate and effective for these younger patients, to accompany existing evidence that suggests that recommendations to diminish the high consumption of fat and sugar among young adults  may be bIn conclusion, diabetes remains a public health emergency in Mexico that continues to grow. Comprehensive policies and strategies to further improve the quality of diabetes care are needed, with more emphasis on preventive approaches and the non-pharmacological management of patients, and with increased proactivity among health professionals.


Halisarca dujardini. The objectives of this work are to detect the cells and morphogenetic processes involved in Halisarca regeneration. We show that in Halisarca there are three main sources of the new exopinacoderm during regeneration: choanocytes, archaeocytes and (rarely) endopinacocytes. Here we show that epithelial-to-mesenchymal transition (EMT) and mesenchymal-to-epithelial transition (MET) occur during Halisarca regeneration. EMT is the principal mechanism during the first stages of regeneration, soon after the injury. Epithelial cells from damaged and adjacent intact choanocyte chambers and aquiferous canals assume mesenchymal phenotype and migrate into the mesohyl. Together with archaeocytes, these cells form an undifferentiated cell mass beneath of wound, which we refer to as a blastema. After the blastema is formed, MET becomes the principal mechanism of regeneration. Altogether, we demonstrate that regeneration in demosponges involves a variety of processes utilized during regeneration in other animals  and points to the particular importance of transdifferentiation in this process. Further studies will be needed to uncover the molecular mechanisms governing regeneration in sponges.The ability to regenerate is widespread in the animal kingdom, but the regenerative capacities and mechanisms vary widely. To understand the evolutionary history of the diverse regeneration mechanisms, the regeneration processes must be studied in early-evolved metazoans in addition to the traditional bilaterian and cnidarian models. For this purpose, we have combined several microscopy techniques to study mechanisms of regeneration in the demosponge  Regeneration is a biological phenomenon which is critical for the survival of an organism. Reparative regeneration is widely distributed among metazoans, with both similar and divergent cellular and morphogenetic mechanisms utilized within and among different taxa . To undeThe regeneration of injured or lost body parts is particularly common in epifauna, and is essential for community recovery from external disturbances that damage these animals . SpongesA large number of studies on regeneration in Porifera, carried out in the last decade, were performed on somatic cell conglomerates called primmorphs  is a convenient sponge for studying regeneration. It is a common species in littoral habitats along the European coasts from the English Channel to the White Sea  were collected in the White Sea  in June–July 2010–2012 and in April of 2010 and March of 2011 near island Sotra in the North Sea . Sponges were collected with their algal substrate and maintained in aquariums with sea water at +12 °C in the Marine Station of the Zoological Institute RAS  and in the Sars International Center for Marine Molecular Biology .Sponges No specific permissions were required for these locations because the study was done outside of the national park, private land or protected area. We confirm that the field studies did not involve endangered or protected species.Manual dissections were performed with the aid of a stereomicroscope and use of Castroviejo scissors and microscalpels. For each experiment, a portion of apical ectosome  was removed, along with a directly underlying section of the aquiferous system . The depth of excision varied slightly between the operations, from 150 to 500 µm. The osculum  remained intact in all cases. Wounded sponges were maintained in 40 mm Petri dishes with 0.22 µm-filtered sea water replaced daily. Six individuals were observed for each time point at various intervals until regeneration was complete. Timing was started from 0 h (wounding); regeneration was monitored under a dissecting microscope and specimens were fixed at 3, 6, 12, 24, 48 and 72 h after excision.4 in seawater at room temperature for 2 h. After fixation, samples were washed in 0.2 M cacodylate buffer and distilled water successively, and finally dehydrated through a graded ethanol series. For semi thin sections and transmission electron microscopy (TEM) specimens were embedded in Araldite resin. Semi thin sections (1 µm in thickness) were cut on a Reichert Jung ultramicrotome equipped with a diamond knife “Micro Star” 45°, then stained with toluidine blue, and observed in a WILD M20 microscope. The digital photos were made on a Leica microscope DMLB with the system of photo capture Evolution LC color. Ultrathin sections (60–80 nm) were cut with a Leica UCT ultramicrotome equipped with a diamond knife Drukkert 45°. Ultrathin sections, contrasted with uranyl acetate, were observed under a Zeiss-1000 transmission electron microscope (TEM). For scanning electron microscopy (SEM), fixed specimens were critical-point-dried, sputter-coated with gold-palladium, and observed under a Hitachi S 570 SEM.For microscopic investigation sponges were fixed in a solution composed of one volume of 25% glutaraldehyde, four volumes of 0.2 M cacodylate buffer and five volumes of filtered seawater for 2 h and post-fixed in 2% OsOFor labeling of newly synthesized DNA we used 5-Ethynyl-2′-deoxyuridine , which is incorporated into genomic DNA during S-phase . A serie® EdU Alexa Fluor® 488 Imaging Kit  according to manufacturer instructions, and then incubated in mouse anti-tubulin antibody  at 4 °C overnight. Specimens were then rinsed three times in blocking buffer during 3–5 h at while rotating and incubated in Alexa Fluor® labeled anti-mouse secondary antibody . After 12 h of incubation in the secondary antibody, specimens were rinsed and the DNA was stained with TO-PRO® -3  at concentration 1 µM in PBS during 2 h. Rinsed samples were mounted in DABCO-glycerol and images obtained using a multiphoton confocal microscope Leica TCS SP5 MP with white laser WLL. Pictures processed with LAS AF Lite  and ImageJ software (http://imagej.nih.gov/ij/).Specimens at different stages of regeneration and immediately after wounding were fixed in 4% paraformaldehyde in PBS  for 1 h followed by washing in PBS. Fixed and rinsed specimens were blocked in 5% normal sheep serum/0.05% Tween-20 in PBS during 1 h at room temperature. Specimens were treated with the Click-iTHalisarca dujardini is a predominantly shallow water, encrusting sponge growing up to 0.5–4 cm in diameter with thickness of 0.5–12 mm , II—wound healing and formation of a “blastema” (12–36 h), and III—restoration of ectosome and choanosome (36–72 h).The observed regeneration processes in Sections of ectosome together with the directly adjacent choanosome were surgically removed at the beginning of the experiment . ImmediaDuring the initial six hours after injury, the “regenerative plug” forms at the wound area. It consists of exudate (mucus), bacteria and cell debris, and includes dedifferentiated pinacocytes, choanocytes, spherulous and granular cells of the mesohyl  and 3D. At 12 h after injury, the wound surface is completely covered with exudate and ECM  and 4B, 24 h after wounding, the ectosome is composed of a well-developed dense collagen layer, which is comparable to that of the intact ectosome  and 8B.Archaeocytes, which are toti- or pluripotent cells of demosponges , and theDifferentiation of exopinacocytes is individual, and begins with cells migrating from the blastema towards the wound surface. Upon reaching the wound, the cells flatten, assuming positions parallel to the surface  and 5D. At 24 h after injury, the part of choanosome which is underlying the wound remains anarchized, presenting as an accumulation of individual cells rather than continuous epithelium . These cAt 48 h after injury, many newly differentiated exopinacocytes are present at the wound surface, but a continuous exopinacoderm has not yet formed . NumerouDuring regeneration of the choanosome, the aquiferous canals and choanocyte chambers form by association of previously disaggregated endopinacocytes and choanocytes, respectively  and 7E. Scar-free wound healing is complete approximately 72 h after the injury . At thisCells of intact sponges actively incorporate EdU, and after 6 h, labeling nuclei of numerous cells—mainly choanocytes—become marked  and 9B. Many of the choanocytes migrating towards the wound surface after 6 h of regeneration have labeled nuclei  and 9F. During the reorganization of the aquiferous system between 24 and 48 h following wounding, labeled choanocytes and mesohyl cells are randomly distributed around the wound . Thus, aHalisarca dujardini regeneration follows a sequence of events previously reported for other demosponges (In this work we show that in osponges : (1) cloThe starting point of eumetazoan regeneration is the healing of the wound, which often involves migration of epithelial cells toward the site of injury .Halisarca dujardini, partial epithelialization of the wound takes place within the first 24 h of regeneration, and is completed within 3 days  also detected within its mesohyl. These findings are consistent with the data available for other demosponges. Study of the choanocyte chamber formation in the freshwater sponge Ephydatia fluviatilis showed that choanocytes were rapidly dividing  endopinacocytes , soon after the injury. Epithelial cells (choanocytes and endopinacocytes) from damaged and adjacent intact choanocyte chambers and aquiferous canals assume mesenchymal phenotypes and migrate into the mesohyl. After the blastema is formed, MET becomes the principal mechanism utilized during regeneration of the ectosome and the upper part of choanosome.Here we show that EMT and MET occur during Our study demonstrated that regeneration in demosponges involves a variety of processes utilized during regeneration in other animals  and points to particular importance of transdifferentiation in this process. Further studies will be needed to uncover molecular mechanisms governing these processes.


HLA locus was greater compared to population stratification correction methods. SNPClust will enable the use of ancestry-independent genetic information in the reclassification of Systemic Autoimmune Diseases. SNPClust is available as an R package and demonstrated on the public Human Genome Diversity Project dataset at https://github.com/ThomasChln/snpclust.Systemic Autoimmune Diseases, a group of chronic inflammatory conditions, have variable symptoms and difficult diagnosis. In order to reclassify them based on genetic markers rather than clinical criteria, we performed clustering of Single Nucleotide Polymorphisms. However naive approaches tend to group patients primarily by their geographic origin. To reduce this “ancestry signal”, we developed SNPClust, a method to select large sources of ancestry-independent genetic variations from all variations detected by Principal Component Analysis. Applied to a Systemic Lupus Erythematosus case control dataset, SNPClust successfully reduced the ancestry signal. Results were compared with association studies between the cases and controls without or with reference population stratification correction methods. SNPClust amplified the disease discriminating signal and the ratio of significant associations outside the  The PRECISESADS project aims at reclassifying Systemic Autoimmune Diseases (SADs), a group of chronic inflammatory conditions characterized by the presence of unspecific autoantibodies in the serum and serious clinical consequences, based on genetic and molecular biomarkers rather than clinical criteria. SADs affect 1% of the global population [Several technological platforms are used to generate biomarker data from patient samples, to obtain as much information as possible about the genetic and molecular mechanisms involved. The technologies include Single Nucleotide Polymorphisms (SNPs) microarrays, which measures hundreds of thousands of common genetic variations in a population, gene expression and protein microarrays, mass spectrometry for metabolic profiling, or flow cytometry, as examples. The methodological approach is to first analyze data from each technological platform individually and then to merge relevant features from each platform to build the final classifier. Here we present the results of the preparatory work for SNP clustering analysis performed on a test dataset.Familial and twin studies have estimated a 50% genetic component in SADs , 3 and GSNPClust first applied PCA to project patients on the largest sources of variance by linear combinations of SNPs. Then for each principal component, the SNPs that had significantly high contributions were selected. Many correlated SNPs were selected from specific loci due to linkage disequilibrium between SNPs, which form haplotypes, and therefore still produced an ancestry signal. To address this, for SNPs selected from the same principal component, SNPClust summarized physically close SNPs in linkage disequilibrium by one variable inferring a haplotype, and reduced the ancestry signal while conserving the other underlying genetic signals.The test dataset contained SNP microarray data from 4,212 European SLE patients and 1,221 European controls. After quality control, Minor Allele Frequency (MAF) filtering, and tag SNP selection , PCA wasOn the SNPClust selected dataset, the clustering signal due to ancestry was significantly reduced. The performance of SNPClust was compared to GWAS standard approaches and reference population substructure correction methods , 10. SNPAs expected, PCA applied on the input dataset (without any prior feature selection or data transformation) grouped patients by the country of origin of the samples, discriminating Northern from Southern Europeans in the first principal component and Eastern from Western Europeans in the second .This ancestry signal can also be seen in most of the 10 first principal components. The most important non-ancestry-based source of genetic variation in the PCA appeared on principal component 3 (see below), thus confirming that the ancestry signal is much stronger than clinically relevant signals in clustering approaches.HLA locus was the strongest and largest contributor in all of the first 8 principal components except principal component 3. Principal component 3 was driven by the chromosome 8 locus 8p23, one of the largest inversion polymorphism encompassing 4,500,000 base pairs and including the SLE associated gene BLK [8p23 was a main contributor in some of the first principal components, we confirmed that ancestry-independent signals can be extracted by SNPClust.The analysis of the contributions of SNP markers to the PCA principal component axes revealed that the first twenty principal components were driven by large localized SNP groups. The chromosome 6 gene BLK  Fig 2)..HLA locuThe 100 first principal components, on which the Gaussian mixture models based selection was applied, explained 3.5% of the total variance. Large localized SNP groups were selected along with other strong contributors. In total, 10,422 SNPs were selected, including 4,090 SNPs from the first 8 principal components .Then, the 10,422 selected SNPs were reduced to 261 SNPs and 331 haplotypes by the haplotype estimation process described in the methods. For example, on principal component 3, the 875 SNPs from chromosome 8 were summarized by 2 distinct haplotypes h1 and h2. Each subject was assigned a h1/h1, h1/h2, or h2/h2 haplotype combination for this region .We applied PCA on the selected SNPs and haplotypes. The first principal components did not cluster patients neither by phenotype nor by centers .The method therefore reduced the ancestry signal and produced a set of features that could be further investigated for disease relevant signals.GWAS have found several loci associated with SADs. However such approaches are impaired by population substructures that can generate false-positives or domestic association signals . In ordevs. 222. In addition, the initial selection of SNPs by SNPClust reduced the impact of the multiple testing correction: 59% of SNPs on the input dataset with p < 0.05 had a False Discovery Rate (FDR) [Compared with the GWAS performed directly on the input dataset, the GWAS performed on the SNPClust-processed dataset selected much less SNPs with a nominal p-value < 0.05: 97,066 te (FDR)  > 5%, coHLA region. Therefore SNPClust has less statistical power than genomic control but is much more effective in finding associations from several loci. Eigenstrat [HLA (24% vs. 55% and 32%).Compared with GWAS with genomic control , SNPClusgenstrat  was perfIncreasing statistical power can increase false positive rate. However SLE has still a large unexplained heritability and increasing the power is a possible step to reduce it by discovering novel markers. Additionally, the FDR multiple testing correction method can also be more stringent to reduce the power and the false positive rate.HLA locus exhibited a pitfall of GWAS with multiple testing correction: even after TagSNP selection, most associated SNPs were from few loci, due to haplotypes. This had the effect of excluding other loci when multiple testing correction was applied. SNPClust overcame this by summarizing the SNPs from one locus in one haplotype. Associated genes found by SNPClust and Eigenstrat with 5 components were compared. SNPClust had 67 unique genes associated, Eigenstrat had 37, and with an intersection of 1. The associated genes were also compared to previously known genes associated with SADs. The intersection had 1 known gene (NOTCH4). Excluding this one, SNPClust had 4 known genes  and Eigenstrat 4 .The HLA locus is involved. Therefore removing simply the main known ancestry-informative markers may lead to the removal of clinically relevant SNPs while preserving many SNPs carrying small bits of ancestry information. Approaches considering the first principal components to adjust associations [The ancestry information is contained in many SNPs across the genome, and may therefore be present in clinically relevant SNPs, in particular in auto-immune diseases where the ciations  can alsoSNPClust overcomes these limitations in two steps. First the major contributors to a large number of the first principal components are considered, therefore selecting the markers explaining most of the variance in the dataset. This has the property of preserving the largest sources of genetic variation. Then, the SNPs that could be considered as haplotypes due to their correlation and spatial proximity are summarized. This reduces the relative importance of ancestry information present in many SNPs while preserving the information conveyed by the haplotypes. At the same time, it also reduces the multiple-testing problem.In the dataset of 379,190 SNPs from SLE patients and controls, the first principal components were associated with ancestry. After application of SNPClust 592 markers remained and the first principal components were not associated to the centers. Therefore the ancestry information and the number of markers were strongly reduced.HLA locus. Compared to Eigenstrat, SNPClust had more statistical power and a higher ratio of associations outside HLA. Therefore SNPClust is useful to find several associated loci without being overwhelmed by strong signals from one single locus such as HLA.This method is also interesting for GWAS, due to the enrichment of ancestry-independent markers tested and the reduced multiple testing problem. When compared to genomic control, 42% less SNPs were associated with the diseases but 10 times more outside the https://github.com/ThomasChln/snpclust.SNPClust will be applied to the SNP array data generated in the PRECISESADS project and will possibly enable the use of ancestry-independent genetic information in the reclassification of SADs. It is available as an R package and demonstrated on the public Human Genome Diversity Project dataset  at httpsThe dataset contained 4,212 European SLE patients and 1,221 European healthy controls. It was previously published  and appr2r > 0.8, window of 500,000 base pairs). The missing values were imputed by random sampling of each SNP. Then each SNP was centered and scaled to unit variance.Observations with missing value rates above 3% and SNPs with missing value rates above 1% were excluded. An additive genetic model is then used  and SNPs with MAF below 5% were excluded to remove rare variants, which are more prone to genotyping errors. In addition, in order to decrease the required computation time and memory usage, redundant SNPs were removed by applying TagSNP .For each principal component, a Gaussian mixture model  with 2 mAlgorithm 1 Selection of strong contributorsInput: PCA rotation matrix i.e. SNPs coefficients to principal components1: forcoefficientsincoefficientsPC1, …, coefficientsPC100do2: coefficients ← 3,000 highest absolute values of coefficients3:  selection ← ∅4:  fornmixturesin 2, 3, 4, 5 do5:  GMM ← Gaussian mixture model of nmixtures components on coefficients6:   selection ← coefficients with null uncertainty classification in GMM7:   if Number of chromosomes in selection < = 8 then8:   exit for loop9:    end if10:   end for11:  storeselectionin output12:  end for13: Output:selectionPC1, …, selectionPC10014: In a second step, in order to summarize large loci, for each principal component, selected SNPs on a same chromosome and closer than 1,000,000 base pairs away were summarized by haplotypes, pairs of binary values. Haplotypes were inferred with the SHAPEIT software  which usAlgorithm 2 Summarization of physically close SNPsInput: Selected SNPs for the 100 first principal components1: haplotypes ← ∅2: forSNPsinselectionPC1, …, selectionPC100do3: forlocusin groups of SNPs closer than 1,000,000 base pairs in SNPsdo4:  haplotype ← Haplotype estimation of locus5:   SNPs ← Exclude locus from SNPs6:   storehaplotypeinhaplotypes7:   end for8:  end for9: forhaplotypesin groups of haplotypes from same chromosome do10: haplotypes ← Squared correlation threshold of 0.8 on haplotypes11:  end for12: Output: Union of haplotypes and SNPs13: To evaluate the SNPClust algorithm, we performed a GWAS on the SNPClust selected dataset and on the input dataset with and without population stratification correction. First, a generalized linear model with a binomial error distribution was fitted to each SNP and haplotype to predict the disease of patients. Type 2 Analysis of Variance was then applied to obtain p-values.Multiple testing correction was performed with FDR, and results were compared with the outcome of our method. Then, two population stratification correction methods were tested, genomic control and Eigenstrat.


Quantitation was achieved with UV detection at 270 nm. The method was validated in terms of accuracy, precision, linearity, limits of detection, limits of quantitation, and robustness. This optimized method has been successively applied to pharmaceutical formulation and no interference from the tablet excipients was found. TDF, EMT, and RPV and their combination drug product were subjected to acid, base, neutral hydrolysis, oxidation, dry heat, and photolytic stress conditions and the stressed samples were analyzed by the proposed method. As the proposed LC method could effectively separate the drugs from its degradation products, it can be employed as stability-indicating method for the determination of instability of these drugs in bulk and commercial tablets. A simple, accurate, rapid, and stability-indicating RP-HPLC method for a combination of tenofovir disoproxil fumarate, emtricitabine, and rilpivirine has been developed and subsequently validated in commercial tablets. The proposed HPLC method utilizes Phenomenex Gemini C18 column (150 mm × 4.6 mm i.d., 5  Safety and efficacy of pharmaceuticals are two basic problems with importance in drug therapy. Instability of pharmaceuticals can cause a change in physical, chemical, pharmacological, and toxicological properties of the active pharmaceutical ingredients (API), thereby affecting its safety and efficacy. Hence, the pharmacists should take cognizance of various factors such as drug stability, possible degradation products, mechanisms and routes of degradation, and potential interactions with excipients utilized in the formulation to ensure the delivery of their therapeutic values to patients. In order to assess the stability of a drug product, one needs an appropriate analytical methodology, the so-called stability-indicating methods which allow accurate and precise quantitation of the drug and its degradation products and interaction products, if any. In recent times, the development of stability-indicating assays has increased dramatically using the approach of stress testing as enshrined in ICH guideline  and evenEMT, a synthetic nucleoside analog of cytidine, is phosphorylated by cellular enzymes to form EMT 5′-triphosphate. EMT 5′-triphosphate inhibits the activity of the HIV-1 RT by competing with the natural substrate deoxycytidine 5′-triphosphate and by being incorporated into nascent viral DNA which results in chain termination.TDF is an orally bioavailable ester prodrug of tenofovir , an acyclic nucleotide analog with activity in vitro against retroviruses, including HIV-1, HIV-2, and hepatitis B virus (HBV). Due to the presence of a phosphonate group, TDF is negatively charged at neutral pH, which limits its oral bioavailability. Following absorption, TDF is rapidly converted to tenofovir which is metabolized intracellularly to the active metabolite, TDF diphosphate, a competitive inhibitor of HIV-1 RT that terminates the growing DNA chain. Acyclic phosphono-methyl ether nucleosides like TDF exhibit distinct biological properties. Due to their efficient intracellular activation to their active metabolites, they possess potent antiviral activity in vivo [RPV is a second generation nonnucleoside reverse transcriptase inhibitor (NNRTI) for the treatment of HIV. It has higher potency, longer half-life, and reduced side-effect profile compared with older NNRTIs such as efavirenz. It has demonstrated activity against NNRTI resistant viral strains due to the flexibility of interactions with the HIV RT .Highly active antiretroviral therapy (HAART) has brought new hope for those people who live with HIV/AIDS by decreasing the morbidity and mortality among people infected with HIV. Highly active antiretroviral therapy also has improved the quality of life among the people who live with HIV/AIDS . The fixLiterature indicates that spectrophotometry –11, HPLCSimilarly, for EMT individually and in combination with other drugs by UV , HPLC inA detailed literature survey for RPV revealed that few analytical methods are available using Spectrophotometry , HPLC 2 and HPTLHence, recently, we have developed an optimized reversed-phase HPLC method for the routine quality control analysis of EMT, TDF, and RPV simultaneously from tablets. The method gave acceptable results for fresh quality control samples but gave overestimation during analysis of stability samples and aged products, as it lacks assay specificity in the presence of their degradation products. Further, no stability-indicating method has been reported in literature for simultaneous determination of EMT, TDF, and RPV in presence of their degradants.Therefore, the present study targets the development and subsequent validation of a stability-indicating assay of new RP-HPLC method for the simultaneous determination of EMT, TDF, and RPV in presence of interaction/degradation product.Analytical pure samples of emtricitabine , tenofovir disoproxil fumarate , and rilpivirine  were used in this study. The pharmaceutical dosage form used in this study was Complera procured from the local market and labelled to contain 200 mg of emtricitabine, 300 mg of tenofovir disoproxil fumarate, and 25 mg of rilpivirine per tablet. The solvent of acetonitrile (MeCN) was of HPLC grade and potassium dihydrogen phosphate, sodium hydroxide, hydrochloric acid, hydrogen peroxide, and triethylamine were of analytical reagent grade purchased from Merck, India. The HPLC grade water was prepared by using Milli-Q Academic, Millipore, Bangalore, India.μm) column as stationary phase with isocratic mode.The LC system of Shimadzu model with UV-visible detector (SPD-10A) was used for this study and chromatographic separation was achieved on Phenomenex C18  connected with a Phenomenex C18 guard cartridge . The mobile phase consisted of MeCN—potassium dihydrogen phosphate buffer —and triethylamine. Wavelength of 270 nm was selected for detection. The injection volume of the sample was 20 μL. The HPLC system was used in an air-conditioned laboratory atmosphere.Chromatographic separations were carried out on a Phenomenex C18 analytical column , 84 (TDF), and 7 (RPV) μg/mL, which was based on their label strength in tablets.The marketed Complera tablets containing 200 mg of EMT, 300 mg of TDF, and 25 mg of RPV were subjected to various forced degradation conditions to effect partial degradation of the drug preferably in 2–30% range , 30. TheSolutions for acid degradation studies were prepared in mobile phase and 0.3 N hydrochloric acid at room temperature for 24 hrs and mixture was neutralized and the resultant solutions were analyzed after 5–10 min of preparation.Solutions for base degradation studies were prepared in mobile phase and 0.1N sodium hydroxide at room temperature for 2 hrs and mixture was neutralized and the resultant solutions were analyzed after 5–10 min of preparation.Solutions for neutral degradation studies were prepared in mobile phase and water and the resultant solutions heated on a water bath at 90°C for 20 min. The mixture was neutralized and then allowed to cool at room temperature, filtered using syringe filters, and analyzed after 5–10 min of preparation.Solutions for use in oxidation studies were prepared in mobile phase and 8% hydrogen peroxide at room temperature for 5 hrs and the resultant solutions were filtered using syringe filters and analyzed after 5–10 min.Solutions for photostability studies were prepared in mobile phase and the resultant solution was exposed to natural sunlight during the day time for 8 hrs for 3 days. The degraded sample was then filtered using syringe filters and analyzed.Tablets and API in powder forms were exposed to dry heat (60°C) in an oven for 24 hrs. The API and tablet powders were then removed from the oven and an aliquot of tablet powder equivalent to the weight of one tablet was prepared for analysis as previously described.μm) and mobile phase consisting of MeCN—potassium dihydrogen phosphate buffer —and triethylamine 58.72 : 41.23 : 0.05 (v/v) for the separation of EMT, TDF, and RPV without affecting the stability of these analytes. However, this method does not give data on specificity for the estimation of the three analytes in the presence of their degradants. Therefore, as an attempt to develop stability-indicating assay, the same optimal chromatographic condition has been tried to separate these analytes from the degradation products generated during forced degradation studies. Using this customized optimized method, it was possible to separate EMT, TDF, and RPV and their degradation products without any interference and thus the assay can be considered stability-indicating.Our earlier HPLC method was optimized with respect to mobile phase composition, buffer concentration, and flow rate to achieve an optimal chromatographic condition for the separation and simultaneous quantification of EMT, TDF, and RPV from Complera tablet containing EMT 200 mg, TDF 300 mg, and RPV 25 mg. This optimized method employs Phenomenex Gemini C18 column  were carried out under various stress conditions.1: the degradation product of RPV.The extents of degradation of the three analytes in Complera tablet are shown in Labeling of all degradation products was done by a degrading individual drug with a similar condition as used for the combination tablets. Retention time and wavelength of degradation product were useful parameters to label degradation products. Such labeling was very useful to identify common degradation products among different degradation conditions.All three APIs and tablet showed no degradation in 0.1 N HCl at room temperature for 24 hours; therefore, drastic condition was experimented with the use of higher concentration of HCl and reflux. EMT and TDF were easily susceptible to degradation in comparison to RPV in drastic condition and TDF and EMT undergo 18% and 16% decomposition under acidic stress condition for both pure and tablet dosage form. Similarly, RPV undergoes 3% decomposition under the same condition for both pure and tablet dosage form.All drugs showed sufficient degradation when subjected to milder stress conditions of 0.1 N NaOH at room temperature for 2 hours. TDF was comparatively more prone to degradation under basic conditions. TDF underwent complete degradation when higher stress conditions were used. TDF undergoes 31% decomposition under basic stress condition whereas EMT and RPV undergo 17% and 7% degradation for both pure and tablet dosage form. RPV was quite stable under neutral degradation due to its nonpolar nature whereas TDF and EMT undergo 11% and 7% degradation, respectively, for both APIs and tablet dosage forms.2O2 at room temperature for 5 hrs. EMT, TDF, and RPV in APIs and tablets were moderately stable showing 12%, 13%, and 7% degradation, respectively.In oxidation stress condition, lower concentration of oxidizing agent was insufficient to give sufficient degradation for RPV even after prolonged exposure. Hence, samples were stressed at harsher conditions of 8% HIn photolytic degradation, APIs and tablets were exposed to direct sunlight at 8 hours for 3 days. EMT, TDF, and RPV in APIs and tablets were highly stable and they undergo degradations of 2%, 6%, and 1%, respectively. Similarly, in thermal degradation subjected to dry heat (60°C) in an oven for 24 hours, EMT, TDF, and RPV in APIs and tablets were highly stable and they undergo degradations of 2%, 5%, and 1%, respectively. The degradation products of EMT, TDF, and RPV were found to be similar for all the formulations (Complera tablet) and API powders assessed.The stability of stock solutions (stored at 2–8°C and at ambient temperature for 3 days) was determined by quantitation of each drug in solution in comparison to the response obtained for freshly prepared standard solutions. No significant changes (<2%) were observed for the chromatographic responses for the stock solutions analyzed, relative to freshly prepared standards.The degradation study was not intended to identify the degradation products but merely to show that they would not interfere if and when they present. To conclude, the results of stress testing studies indicate a high degree of specificity of this method for EMT, TDF, and RPV.The optimized HPLC method for the analysis of fresh quality control samples was validated in accordance with the ICH Q2 (R1)  guidelinThe sensitivity of the HPLC method that uses UV detection depends upon the proper selection of the wavelength. The standard solutions were scanned from 200 to 400 nm and the overlain UV spectra obtained were recorded . From thThe results of forced degradation studies of each drug in the presence of their degradation products indicated a high degree of specificity of this method for EMT, TDF, and RPV. The degradation product of each of the parent peaks was found to be similar for the Complera tablet compared to that of API powders assessed. Typical chromatograms obtained following the assay of untreated and stressed samples of API and formulations are shown in Accuracy of the method was determined by performing the recovery experiment at 50, 100, and 150% levels of the labeled number of the analytes in the commercial formulation. The recoveries for EMT, TDF, and RPV were found to be 99.50, 99.90, and 99%, respectively, which were within acceptable ranges of 100 ± 2%. The results are presented in The %RSD values for the intraday and interday precision were ≤2% confirming that the method was sufficiently precise. The results are presented in R2) were found to be more than 0.999 for all the analytes. Typically, the means of the regression equations were y = 87545x + 15731, y = 41493x + 18505, and y = 23045x + 65860 for EMT, TDF, and RPV. The LOD and LOQ were estimated as 1.90 and 0.43 ng/mL for EMT, 2.18 and 0.54 ng/mL for TDF, and 3.12 and 1.78 ng/mL for RPV.The linearity was established over the ranges of 28–84, 42–126, and 3.5–10.5 for EMT, TDF, and RPV, respectively. Correlation coefficients , mobile phase ratio (±2%), flow rate (±0.1 mL), and pH (±0.05), but these changes did not affect the method results. The %RSD for the tablets were <2, indicating the robustness of the analytical methodology. The results are presented in A study was conducted to determine the effect of variation in analyst to analyst, lab to lab, and instrument to instrument in triplicate measurement as per the assay method. %RSD was calculated for each condition and results are presented in The optimized and validated formulation assay method was applied to the quantitative analysis of commercial tablet (Complera) and was evaluated by the proposed HPLC method. Good agreement was found between the assay results and the label claim of the product. The %RSD for the tablets were <2, indicating the precision of the analytical methodology. The results are presented in An isocratic stability-indicating HPLC-UV method has been developed for the estimation of EMT, TDF, and RPV in the presence of degradation products. The proposed method is simple, accurate, precise, and specific and has the ability to separate the drugs from degradation products and excipients found in the pharmaceutical dosage forms. The method is suitable for use in routine analysis of both drugs in bulk API powder or in pharmaceutical dosage forms. The method can be applied even to the analysis of stability samples obtained during accelerated stability experiments, as no interference was found with the degradants formed under various stress conditions.