Describe the prevalence of HPV genotypes via PCR and DNA sequencing in 397 women who attended to the gynecological outpatient center in the Hospital Regional Docente de Cajamarca from March to September 2017.A positive PCR result for HPV was observed in 121 cervical samples. A high-risk genotype was found in 63.6% (77/121) of patients, a probably oncogenic type in 23.1% (28/121) and a low-risk type in 7.4%. Among the high-risk genotypes, HPV-31 was the most common one present in 20% (21/77), followed by HPV-16 in 11.4% (12/77). Coinfections between two or more genotypes were observed in 12 cases.The online version of this article (10.1186/s13104-018-3644-7) contains supplementary material, which is available to authorized users. Cervical cancer is the second leading cause of female cancer mortality in Peru accounting for more than 1700 deaths annually , 3. HPV HPV genotypes identified in women with cervical cancer are traditionally classified based on their associated risk of malignancy , 6. ThusAfter over 30 years of screening services and with cervical cancer declared a national priority in 2000, HPV infections remains a major concern in Peru especially affecting underserved areas where surveillance is limited –12. The Hospital Regional Docente de Cajamarca, Peru. Women attending the gynecological outpatient center who had a history of at least 1 sexual encounter were studied from March to September 2017. Patients were excluded if there was evidence of pregnancy, severe gynecological bleeding, hysterectomy or previous history of HPV-related disease including cancer, warts and other cutaneous manifestations.A consecutive cross-sectional study was conducted in the Hospital Regional Docente de Cajamarca and Universidad Peruana de Ciencias Aplicadas. Once the outpatient consultation ended, the attending physicians informed the patients about the study purpose and asked for written consent before enrollment. After a standardized questionnaire was completed by the physician a cervical sample was collected for further analysis. The questionnaire includes the following data: age, marital status, age of first sexual intercourse, number of sexual partners, sexual partners in the last 6 months, extramarital sexual relations, history of sexually transmitted infection (STI), abortions, Number of births, use of condoms, last pap, personal and family history of cervical cancer, use of sex toys, history of sexual abuse and date of the Last Papanicolaou test.This study has been approved by two independent Ethics Committees: Universidad Peruana de Ciencias Aplicadas. Once samples arrived at the laboratory, the cytobrushes were discarded and the tubes were vortexed and centrifuged to pellet the cells, which were resuspended in 1 mL of phosphate buffered saline. Three aliquots of each fresh specimen were stored at − 20 °C until testing.Cervical cell samples from the ectocervix and endocervix were collected from each woman using a cytobrush for preservation in a tube containing phosphate buffered saline (pH 8.6). The samples were then stored at − 4 °C and sent to the Molecular Biology Laboratory at Viral genomic DNA was extracted from a total volume of 200 μL of the sample by the guanidinium thiocyanate extraction method  and the Human papillomavirus amplification was done using the primers and conditions described by Lurchachaiwong et al. . PCR proethidium bromide and bands were detected by UV transillumination . Positive specimens were confirmed by direct sequencing serving as the gold standard (Macrogen-Korea).The HPV genotypes were categorized into three groups: high, probably oncogenic and low risk based on the IARC classification  .A total of 397 women were studied from March to September 2017. Most patients were between 36 and 45 years old (35%) followed closely by the age group 26–35 years old (30.2%); 51 patients were under 25 years old (12.8%) with only two patients under 18 years old  of patients, a probably oncogenic type in 23.1% (28/121) and a low-risk type in 7.4%; other genotypes were detected in 19.83%. All sequenced genotypes are shown in Table Coinfections between two or more genotypes were observed in 12 cases. The most common coinfections were between HPV types 39–45–68, 40–43–91 and 31–91 each of them in two cases  . Although uncommon, 53.8% of extramarital affairs were observed in this group. Additionally, 19 of these women have never had a Pap smear test for cervical cancer screening  followed by HPV-16 (11.4%). These results differ from a previous investigation our research team conducted in Cajamarca between 2010 and 2012, in which the HPV-16 was the most common genotype in 38.5%, followed by the HPV-39 in 9.6% .Another investigation in 465 women, without the diagnosis of cervical cancer, from Lima, Peru reported the genotypes HPV-16 (23.8%) and HPV-6 (11.9%) . Thus, HMultiple genotypes can be detected in patients with cervical cancer suggesting that coinfections might be a potential risk factor for carcinogenesis. A recently published study from 2017, reported a 4.1-fold higher risk of developing invasive cervical carcinoma in subjects infected with any HPV genotype, excluding HPV-16, in association with HPV-18 . Thus, tGenital HPV infections are spread by unprotected penetrative intercourse or close skin-to-skin physician contact , 23. In The risk of HPV infection in women is directly related to the number of male sex partners. Furthermore, as with other sexually transmitted diseases, sex with a new partner is a stronger risk factor than sex with long-term partners –28. In oIn 2011, Almonte et al. conducted a research in women attending cervical cancer screening in the Peruvian Amazon. In this study, early age at first sexual intercourse and more than 5 sexual partners were risk factors for having HPV infection. More interestingly, high parity, no schooling and the lack of a good-quality screening with an adequate follow-up were the main risk factors for high-grade cervical disease . Even thHuman papillomavirus DNA testing is increasingly being used as it improves the sensitivity for detection of cervical cancer precursors when used in combination with cervical cytology. However, using molecular testing can also decrease specificity resulting in potential unnecessary referrals for colposcopy . AdditioDespite national efforts for cervical cancer screening and prevention, HPV infections resulting in invasive cervical cancer remains a major health issue in Peru. Additionally, in underserved areas such as Cajamarca HPV genotype surveillance is limited. Contrary to previous reports in which HPV-16 was predominant, an increase of HPV-31 have been observed which is now the most common high-risk genotype in our study population.The present study had one important limitations. We designed the study for the detection and genotypification of HPV, thus our results are only for prevalence reporting and the implications of these genotypes or the potential risk for cancer in our patients is unknown. Second, due financial limitations and our study design it was impossible to compare the isolated genotypes with pap smear results as they were not available in most of our patients.Additional file 1: Table S1. Human papillomavirus types and oncogenic potential. Table S2. Demographics and characteristics among women with HPV.


Equivocal lesions (ASC-US) are common abnormalities in cervical cancer screening exams. HPV testing helps to stratify the risk of progression to high-grade squamous intraepithelial lesions or more (HSIL+). Population-based medical electronic data can be used to evaluate screening recommendations. The study uses routine electronic data from primary health centers to estimate the impact of HPV testing in a 3- and a 5-year risk of HSIL+ after an ASC-US. The study includes data derived from medical electronic information from 85,775 women who first attended a cervical cancer screening visit at the National Health System facilities of Catalonia, Spain, during 2010–11 and followed up to 2015. Included women were aged between 25–65 years old, having at least one follow-up visit, and a cervical cytology of ASC-US . Women with a first result of low-grade squamous intraepithelial lesions (LSIL) (N = 945) or those with negative cytology  were included for comparison. Those with a baseline HSIL+ were excluded. Incident HSIL+ was evaluated by means of Kaplan-Meier curves and multivariate regression models. HPV test results were available for 63.4% of women with a baseline ASC-US. Among all ASC-US, 70 incident HSIL+ were identified at 5 years. ASC-US HPV positive women had a high risk of HSIL+ compared to women with negative cytology  and a similar risk to women with baseline LSIL , whereas ASC-US HPV negative women had no differential risk to that observed in baseline negative cytology. Women with ASC-US and no HPV test had an average HSIL+ risk . Population-based e-medical records derived from primary health care centers allowed monitoring of screening recommendations, providing robust estimates for the study outcomes. This analysis confirms that HPV testing improved risk stratification of ASC-US lesions. The information can be used to improve diagnosis and management of screen detected lesions. Equivocal lesions  are common abnormalities detected in population-based cervical cancer screening ,2. HowevIn Spain, a country with historically low rates of invasive cervical cancer, screening has largely been based on conventional cytology under an opportunistic scenario. Systematic evaluation of screening records in the region of Catalonia indicate that abnormal cytology results account for around 3% of cervical cytologies in any given screening round, of which 96.5% are ASC-US or LSIL . At presThis study was approved by the Clinical Research Ethics Committee and the Institutional Review Board of the University Institute for Primary Care Research (IDIAP) Jordi Gol (P15/106).In the region of Catalonia, opportunistic cervical cancer screening is offered for free by the National Health System (NHS) and delivered through the public primary care network. Since 2006, Catalan NHS guidelines established that a 13 high-risk HPV types DNA test  was recommended after a diagnosis of ASC-US within 3 months of the conventional cytology result. Women with an HPV negative test are sent back to a 3-years regular screening schedule while those with an HPV positive result are referred to immediate colposcopy .Specific information for the purpose of this analysis was extracted from the NHS electronic data provided by the Information System of the Primary Health Care facilities (SISAP). The SISAP holds data from 279 Primary Health Centers and 28 Sexual and Reproductive Health Clinics. The SISAP stores the NHS primary care clinical data of approximately 75% of the resident population in Catalonia ,14. We rThe HPV DNA test result was included in the analysis if it was performed within a window of 60 days since the first cytology record. A window of 90 days would have resulted in including additional 62 women of which 52% remained positive. All women with a baseline diagnosis of ASC-H and HSIL+ were excluded from this analysis as these women are referred for immediate colposcopy and treatment.We identified 142,284 women aged 25–65 residing in Catalonia and having a first cervical cancer screening visit during 2010–11 at NHS facilities. Women with a baseline diagnosis of ASC-H or HSIL+ (N = 453) were excluded from this analysis, leaving 141,831 women as the target population. Of them, 85,775 women (60.5%) were included in the final analysis as they had at least one additional screening test up to December 2015 when we closed the study window time. The remaining women  were considered lost to follow-up as they did not return within an interval of 3 years or more after the first cytology. These women were significantly older , and in particular women aged 60–65 years were almost twice as likely not to return for a second exam. Lost to follow-up women were also more likely to be born outside Spain , residing outside Barcelona , and more likely to have a negative screening result at baseline  .Kaplan-Meier curves were used to draw the probability to develop HSIL+ over time. Curves were stratified by baseline screening results and age group: negative cytology, ASC-US HPV positive, ASC-US HPV negative, ASC-US with unknown HPV status, and LSIL and two age groups, < 35 years and 35+. Time to event was measured as person-months from the baseline cytology until an HSIL+ diagnosis or until the last cytology result, within the study period, for the remaining cytology results. Log-rank tests and the Renyi test were used to evaluate subgroup differences between cumulative incidence curves ,18.Multivariable logistic regression models with a complementary log-log binomial regression were used to estimate hazard ratio (HR) of HSIL+ and 95% confidence intervals (CI) .Data analyses were conducted using R  and Stata .≥ 35+ years with the exception of those aged ≥ 35+ years with an ASC-US with unknown HPV result in which the risk of HSIL was of significantly lower compared to that of HPV positive, although it remained high .Using a large population-based data set, the study confirms the predictive value of HPV triage in screen-detected ASC-US for HSIL+. This, to our knowledge, is the first report of these characteristics in Spain and adds to the value of molecular approaches to cervical cancer screening. The data confirm that women with a diagnosis of ASC-US HPV negative had a very low risk of HSIL+ compared to women with a negative cytology and in line with Demarco et al., supporting managing algorithms based on risk estimation . ConversThe similarity in risk for HSIL+ of ASC-US HPV positive and LSIL strongly suggests that management of both entities should be the same as recommended in the European Union guidelines . The guiWe had evidence of 11 invasive cervical cancers among HSIL+, 2 of them arising in the baseline category of ASC-US HPV positive result at age 26 and age 37. The time at diagnosis was 30 and 42 years old, respectively. Most likely, the total number of invasive cervical cancer cases in our series was underestimated as only those cases recorded by the general practitioner could be retrieved. This reporting is not compulsory and thus a comprehensive accountability at the primary health level cannot be guaranteed. Three out of the 11 cervical cancer cases were diagnosed in the 25–34 age group, of which 2 had as a baseline diagnosis a negative cytology and another case had an LSIL. Whether these results justify co-testing with HPV in younger women is a subject of discussion, and cost-efficiency analysis generally do not support this approach as many women would be carriers of acute infections not leading to disease. The aim of screening remains to have a test with high sensitivity followed by a good triage test. Maybe even if HPV is common in this age group, co-testing with automated cytology and HPV testing could provide a better case ascertainment than cytology alone [This study is based on routinely collected medical information at the primary health level. By extracting specific indicators, the data base allowed evaluation of screening practices in the absence of specific screening registries. The analysis presented informed about adhesion to general guidelines and recommendations in a routine clinical environment, covering a large population, both at geographic extent and size, and thus providing real-life estimates. However, drawbacks include information losses and disparities in data collection and clinical management over time or among health care providers. In our case, cytological records could not be comprehensively linked to colposcopy and histological confirmation results. Nevertheless, a substantial number of HSIL+ had an accompanying medical diagnosis qualifying the severity of the lesion underneath the cytology result that certified the result.The consistency of our results with study-based projects indicate that the first step of the screening purposes, to detect HSIL+, has been clearly accomplished within the ASC-US strata particularly when HPV testing is done. It would have been desirable to obtain the full differentiation of CIN2 and CIN3+ of these lesions to evaluate potential overdiagnosis and overtreatment of doubtful cancer precursor lesions as CIN2.The analysis of HSIL+ risk among ASC-US and HPV detection here presented has provided a strong basis to confirm the value of HPV detection for risk stratification and indicate the safety for HSIL+ risk of 5-year interval in negative results. In addition, the data presented will be relevant as baseline information and will allow evaluating future changes in cervical cancer screening policies. While HPV testing has provided an excellent tool to stratify risk in ASC-US, the possible introduction of the HPV test as a primary screening tool may result in larger improvement in risk stratification of participants to screening of cervical cancer. The possibility of setting up a robust data collection system to evaluate triage recommendations is a major achievement under the scope of opportunistic screening. We believe that these results can be of interest to countries that are re-evaluating their cervical cancer screening algorithms from using conventional cytology and moving toward introducing HPV testing.


Balaenoptera physalus) and blue whales (B. musculus) are the two largest species on Earth and are widely distributed across the world’s oceans. Hybrids between these species appear to be relatively widespread and have been reported in both the North Atlantic and North Pacific; they are also relatively common, and have been proposed to occur once in every thousand fin whales. However, despite known hybridization, fin and blue whales are not sibling species. Rather, the closest living relative of fin whales are humpback whales (Megaptera novaeangliae). To improve the quality of fin whale data available for analysis, we assembled and annotated a fin whale nuclear genome using in-silico mate pair libraries and previously published short-read data. Using this assembly and genomic data from a humpback, blue, and bowhead whale, we investigated whether signatures of introgression between the fin and blue whale could be found. We find no signatures of contemporary admixture in the fin and blue whale genomes, although our analyses support ancestral gene flow between the species until 2.4–1.3 Ma. We propose the following explanations for our findings; i) fin/blue whale hybridization does not occur in the populations our samples originate from, ii) contemporary hybrids are a recent phenomenon and the genetic consequences have yet to become widespread across populations, or iii) fin/blue whale hybrids are under large negative selection, preventing them from backcrossing and contributing to the parental gene pools.Fin whales ( Balaenoptera physalus) is a large species of baleen whale. It can grow up to 26 m long and attain a weight of 60–80 metric tonnes [B. musculus) [The fin whale (c tonnes . Like mausculus) . Despiteusculus) ,4. Howevusculus) , Icelandusculus) , and Japusculus) . Furtherusculus) . Male hyMegaptera novaeangliae) [Megaptera was coined based on the derived morphological characteristics of the humpback whale [Although putatively fertile hybrids have been recorded between the two species, the fin and blue whale are not sister taxa. Molecular evidence has shown that the closest living relative of the fin whale is the humpback whale (angliae) ,8,9 , to investigate the extent of hybridisation between fin and blue whales, and whether this hybridisation may have occurred long before the first reported hybrid in the 1800’s. To achieve this, we assembled a fin whale nuclear genome, performed three independent admixture analyses, and in the process, assessed the influence of ascertainment bias based on mapping reference selection.Here, we use publicly available genomic data from four baleen whale species: fin, humpback, blue, and bowhead   from the prinseq , and an  prinseq . We consPdenovo2 , specifyPdenovo2 , utilisiPdenovo2  and genePdenovo2  and the de novo using RepeatModeler version 1.0.11 [Repeats and low complexity DNA sequences were catalogued and masked in the resultant fin whale genome using RepeatMasker version open-4.0.7  using thn 1.0.11  from theOrcinus orca), beluga whale (Delphinapterus leucas), cattle (Bos taurus), dog, (Canis lupus familiaris), humans (Homo sapiens), minke whale , and the finless porpoise  were used for homology-based gene prediction. As no training gene models were available for the fin whale, we used CEGMA [Genome annotation was performed on the repeatmasked genome using the genome annotation pipeline MAKER2 version 2.31.9  with ab-ed CEGMA ,24 to tred CEGMA , rather ed CEGMA . MAKER2 http://www.bowhead-whale.org) as the mapping reference.For use in subsequent analyses, we downloaded raw reads for the humpback whale (SRR5665639) and blue whale (SRR5665644) , both prWe performed three independent analyses to investigate for signatures of admixture between the fin and blue whale based on the known species tree : D-statiWe investigated for signs of unequal shared derived alleles between the blue whale and the fin or humpback whale by performing D-statistics with ANGSD v0.921 . D-statiWe called bases using a consensus base call (-doAbbababa 2), only considered scaffolds over 100kb in length, specified the bowhead whale as the outgroup, and applied the following filters; minimum base quality of 25 (-minQ 25), minimum mapping quality of 25 (-minMapQ 25), only consider reads that map uniquely to one location (-uniqueOnly 1), remove reads deemed “bad” by ANGSD (-remove_bads 1), and specify window size as 1MB (-blocksize). This was repeated twice, once with all three species mapped to the fin whale genome, and once with all three species mapped to the bowhead whale genome.ANGSD performs all possible combinations, but we only considered the output with fin and humpback whales as H1 and H2, respectively, and the blue whale as H3, as this is the known species tree [We conducted three independent 100kb non-overlapping sliding window pairwise distance comparisons . This was repeated twice, once with all three species mapped to the fin whale genome, and once with all three species mapped to the bowhead whale genome. We calculated average pairwise distances from the windows using a consensus base call in ANGSD (-doIBS 2), only considering sites found in all three species (-minInd 3), windows that contained at least 75kb data, and the filters; minimum base quality of 25 (-minQ 25), minimum mapping quality of 25 (-minMapQ 25), only consider reads that map uniquely to one location (-uniqueOnly 1), remove reads deemed “bad” by ANGSD (-remove_bads 1). We constructed the non-overlapping 100kb sliding windows using bedtools , only coTo investigate whether gene flow ceased at different time periods between the fin and blue whale, as opposed to the humpback and blue whale, we used hPSMC . This wa-9 per year. We calculated the average genome-wide pairwise distance between the fin and blue whale and the humpback and blue whale to be the same (0.0128). Using a divergence time of 8.35 Ma [-10 per year.To calibrate the hPSMC plots, we estimated the mutation rates of the fin, humpback and blue whales using the genomes mapped to the fin whale. To calculate the mutation rates of the fin and humpback whale, we performed a genome-wide pairwise distance analysis between the fin and humpback whale using ANGSD. From this, we calculated the mean number of substitutions per year assuming a divergence time between fin and humpback whales of 4.98 Ma . We alsosame 0.018. Using -10 per year, and therefore a mutation rate of 2x10-8 per generation. When comparing the fin/humpback whale, we used a generation 23.7 years, a mutation rate of 1.05x10-9 per year, and therefore a mutation rate of 2.49x10-8 per generation. From the fin+humpback whale hPSMC output, we manually estimated the pre-divergence Ne  to be ~64,000 individuals. We did this by outputting the text file (-R) using the plot perl script from the PSMC toolsuite and looking into the output text file. We then ran simulations using this pre-divergence Ne while specifying various divergence times between 0 and 3 Ma in 100,000 year intervals using ms [The average of the generation times and the mutation rates calculated above were used to calibrate the hPSMC. When comparing the fin/humpback/blue whale we used a generation time of 26.1 years, a mutation rate of 7.7x10using ms . From thWe assembled 2,460,448,386bp  of a female fin whale’s nuclear genome in 59,639 scaffolds with a scaffold N50 of 871.4kb, utilising only publically available data and Cross-Species Scaffolding using the minke whale . InitialThe mapping results of all individuals included in this study to both the fin whale and bowhead whale genomes can be found in We investigated for signs of admixture between the fin and blue whale based on the known species tree by conducting three independent analyses. Each analysis was repeated twice, once with all individuals mapped to the fin whale genome and once with all individuals mapped to the bowhead whale genome.First, we investigated for signs of unequal shared derived alleles between the blue whale and either the fin or humpback whale by performing D-statistics. An excess of shared derived alleles between two species could be indicative of admixture between these species. When using the fin whale genome as the mapping reference, we found slightly more derived alleles shared between the fin and blue whale  compared to the humpback and blue whale . This result gave a D score of -0.0027. However, as the Z score was between -3 and 3 (-1.94), this result was deemed non-significant. In contrast, when using the bowhead whale as the mapping reference, we found more derived alleles shared between the humpback and blue whale  compared to the fin and blue whale , giving a D score of 0.0086 and a significant Z score (6.32).Second, we conducted three independent 100kb non-overlapping sliding window pairwise distance comparisons  and plotted the results, looking for any differences between the supposedly equidistant fin vs. blue, and humpback vs. blue, comparisons. A relative excess of highly similar windows could indicate admixture between the species in question. After filtering, 12,345 windows of at least 75kb of data in all three species remained when mapping to the fin whale, and 17,533 when mapping to the bowhead whale.Regardless of whether the fin whale or the bowhead whale was used as the mapping reference, plots of the 100kb sliding window pairwise distances between the fin vs. blue whale, almost perfectly overlap with that of the humpback vs. blue whale . FurtherOur third analysis for signs of admixture between the fin and blue whale was hPSMC. This analysis makes use of the shared demographic history of the species to uncover the approximate point at which gene flow ceased between the two target individuals. We find that the demographic history of the fin/blue whale pseudodiploid genome is near identical to that produced by the humpback/blue whale , regardlA recent study investigating the nuclear genomes of a number of rorqual whale species suggested that the evolutionary history of rorquals occurred in the presence of introgressive gene flow among species . This geBaleanoptera), the head was more sharply pointed than is usually seen on humpback whales, the dorsal fin was substantially taller and much more erect than other humpbacks, resembling the dorsal fin of a sei whale, and the number of throat pleats (> 44) was nearly two times greater than those of other humpback whales observed and photographed in the area (< 24) [Our D-statistics analyses show conflicting results depending on which mapping reference genome was used. We find no signal of introgressive gene flow in the fin and blue whale genomes when using the humpback whale to control for incomplete lineage sorting and the fin whale as the mapping reference. However, when using the bowhead whale as the mapping reference, we find a significant D-statistic result indicating higher levels of admixture between the humpback and blue whale than the fin and blue whale. These contrasting results could be due to mapping reference ascertainment bias, as fin whale-like reads are more likely to map to the fin whale genome than to the bowhead whale genome, artificially shifting the signals of admixture towards the fin whale. Regardless of ascertainment bias, both results are unexpected; viable fin and blue whale hybrids have been reported since the beginning of whaling in the 1800’s  and are a (< 24) .In contrast to our D-statistics results, our sliding window pairwise distance analysis shows no indication of recent admixture between any of the species, regardless of the mapping reference used. However, these seemingly conflicting results could be explained by ancestral gene flow. Even if gene flow occurred in the past, recombination may have broken up stretches of conspecific DNA, resulting in stretches much shorter than 100kb. D-statistics is much more sensitive to this sort of ancestral admixture, which may have been retained in the humpback whale gene pool at higher frequency due to random chance (i.e genetic drift).To provide more context into these contemporary fin/blue whale hybrids, we investigated signs of ancestral gene flow between all three species pairs, by performing pseudodiploid fin+blue, humpback+blue, and fin+humpback whale joint demographic analyses using hPSMC. We find evidence for the occurrence of ancestral gene flow between the fin+blue whale, and the humpback+blue whale. Using simulation analyses, we find that gene flow ceased between these species pairs 2.4–1.3 Ma  Figs. ThIn contradiction with our finding that gene flow ceased between fin and blue whales >1.3 Ma, Árnason et al 2018 briefly mentioned that current hybridization between fin and blue whales has left genome-wide signals of introgression [in silico mate-pair libraries generated by a closely related species, it also has some limitations. The assembly could contain some mis-assemblies caused by changes in the genomic architecture of the fin and minke whale after they diverged ~10.5Ma [Through the use of a newly assembled fin whale genome and the previously published bowhead whale genome , we were ~10.5Ma  meaning  ~10.5Ma .Our finding of no continual introgressive gene flow between fin and blue whales could have several explanations, linked to both the data used and the biology of the species investigated. First, fin/blue whale hybrids may not occur between the populations our samples originated from. The fin whale individual used in this study is from the North Pacific, where putative hybrids have been reported. The origin of the blue whale is unknown and it could be from a region where hybridization does not occur. To further investigate whether this is the cause of our finding, more individuals of known origin would need to be investigated. Second, hybrids may only be a recent phenomenon, spurred by commercial whaling. Both fin and blue whales suffered large declines in their population sizes during commercial whaling , and mayS1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 TableCoverage was calculated using the total number of bp in each assembly excluding missing data .(DOCX)Click here for additional data file.S1 Fig100kb non-overlapping window identity-by-state, pairwise distance comparisons between each species pair.(DOCX)Click here for additional data file.S2 Fig(DOCX)Click here for additional data file.S3 FigGreyed out regions represent 1.5x and 10x the pre-divergence effective population size, grey lines represent the simulated data in 100kya intervals starting from 1Ma and ending at 5Ma, black line represents the simulations closest to the real data without overlapping it, red line represents the hPSMC result.(DOCX)Click here for additional data file.S4 FigGreyed out regions represent 1.5x and 10x the pre-divergence effective population size, grey lines represent the simulated data in 100kya intervals starting from 1Ma and ending at 5Ma, black line represents the simulations closest to the real data without overlapping it, green line represents the hPSMC result.(DOCX)Click here for additional data file.S5 FigGreyed out regions represent 1.5x and 10x the pre-divergence effective population size, grey lines represent the simulated data in 100kya intervals starting from 0Ma and ending at 3Ma, black line represents the simulations closest to the real data without overlapping it, blue line represents the hPSMC result.(DOCX)Click here for additional data file.


Human papillomavirus (HPV) can infect the epithelium of the esophagus, but so far there is no reliable and comprehensive evidence about the prevalence and association of HPV with esophageal cancer in Iran, as high incidence region. This study aimed to evaluate the prevalence and association of HPV with esophageal squamous cell carcinoma (ESCC) in Iran.Relevant English and Persian articles published up to Aug 2017 and indexed in databases were reviewed. Frequency of HPV genotypes in ESCC cases and controls was surveyed according to regions of Iran. Data were meta-analyzed with random effects models using Comprehensive Meta-Analysis software.P=0.001). In 6 case-control studies, the pooled odds ratio was estimated 1.99 .Overall, 14 studies were eligible including 1444 samples (1062 ESCC cases and 382 controls). HPV was positive in 269 (25.32%) of 1062 ESCC cases and in 65 (17.01%) of 382 controls. Total prevalence of HPV in both groups was estimated 0.256 . The prevalence of HPV-16 and HPV-18 was estimated 0.121 (95%CI: 0.087–0.183) and 0.046 , respectively. The difference in HPV prevalence in different regions of Iran was statistically significant (Q=18.20, df =4, High-risk HPVs were observed in ESCC cases and controls from different regions of Iran. The odds ratio indicates that the HPV infection in ESCC cases was approximately 2 fold more than the controls. More case-control studies in other populations with larger sample size are necessary. Esophageal cancer (EC) is the most offensive malignancy of the gastrointestinal system and the eighth most common cancer worldwide . EC histThe incidence of EC in different parts of Iran was surveyed by the Iran Cancer Institute, 9% of all malignancies and 27% of gastrointestinal malignancies were EC. Golestan Province is one of the high-risk areas, followed by Mazandaran and Khorasan Provinces, all in northeastern of Iran. The incidence of EC from 2005 to 2006 was 5.83 and 6.25 in males and females, respectively. Compatible with other areas of the world, ESCC constitutes more than 90% of all EC in northeastern of Iran  infections, especially with high-risk genotypes including HPV-16 and HPV-18. The evidence of this relationship was weak and the results of these studies are not consistent (The genome of HPV is a double-stranded circular DNA including early (E1 to E7) and late  genes or open reading frames (ORFs) encoding viral nonstructural regulatory proteins and viral structural proteins, respectively. Carcinogenesis of HPV is related to E6 and E7 which deregulate the cellular regulatory proteins (p53 and Rb), therefore leading to proliferation of the host cell. However, E2 has suppression effect on the E6 and E7 promoters. The genome of HPV integrates into the host cell chromosome in malignant tissues and disrupts E2 ORF. Therefore, decreased expression of E2 regulatory protein results in an increased expression of the viral E6 and E7 oncoproteins .Using the sequence of L1 gene, about 200 HPV types have recognized. High risk HPV types including HPV-16 and 18 are more frequent in cancerous tissues, but other types  are less associated with cancers .Some meta-analyses were conducted to estimate the prevalence and association of HPV with ESCC worldwide , 11,12, In addition, molecular studies were conducted about the HPV effect on ESCC in some regions of Iran , 13–15. All studies conducted on the prevalence of HPV in esophageal cancer in Iran were searched systematically from 2002 up to Aug 2017 for relevant articles published in English or Persian languages and indexed in databases such as PubMed, Google Scholar, Magiran, IranMedex, and Iranian Scientific Information Databank (SID). Keywords were “Human Papillomavirus”, “HPV”, “Esophageal Cancer”, “Esophageal Squamous Cell Carcinoma”, “ESCC” and “Iran”. Bibliographies and full texts of studies reporting HPV prevalence in esophageal cancers in Iran were entered into the EndNote software, according to the STROBE Statement-Checklist.1. Studies reporting HPV infection in esophageal cancer and noncancerous tissues in Iran were selected; 2. only full-text studies in English or Persian articles were included.1. Studies that the sampling location was unknown; 2. Studies that do not clearly outline the data; 3. Case report/series; 4. Letter to the editors; 5. Review articles; 6. Abstracts of conferences; 7. Studies that sampling took place at the same time and place reporting the same data.Studies were identified based on the inclusion and the exclusion criteria from all English and Persian language articles reporting the frequency of HPV or its genotypes in esophageal cancers and controls in Iran. All appropriate articles were evaluated by two researchers, independently. With the exclusion of inappropriate studies, the data extracted and entered into an Excel file. If multiple publications reported the same data from the same population, only the publication with newer data was included. Extracted information were including first author, study location (province/city), publication year, if available dates of sample collection, sample size, gender, specimen type, frequency of esophageal cancers (cases), frequency of non-cancerous esophageal tissues (controls), HPV detection method, HPV genotyping method, overall and type-specific frequency of HPV in esophageal cancers (cases), or in non-cancerous esophageal tissues (controls), and grade of malignancy. For studies with samples from multiple province/city, data were extracted separately if possible.2 indexes. The homogeneity was rejected; we used the random-effects model to analyze the publication bias using the Egger test and graph. To estimate the prevalence of HPV genotypes based on age, year of publication, and geographical area, meta-regression was used. At all steps, P-values below than 0.05 were considered statistically significant.Data were analyzed using CMA  software. The effect size was calculated as event rates and their 95% confidence interval. At first, the heterogeneity of the studies was evaluated using the Cochran’s Q and IBased on the preliminary search strategies 261 studies were identified through database searching up to Aug 2017. In addition, four studies were found manually. From 265 studies screened, 248 studies were excluded, including unrelated articles, reviews, case reports, abstracts of conferences, and articles with incomplete information, based on the inclusion and exclusion criteria. Finally, 14 studies were eligible and were included in the meta-analysis . StudiesTotal sample size in 14 studies was 1444, including 1062 esophageal squamous cell carcinomas (ESCC) cases, and 382 esophageal non-cancerous tissues (controls). Esophageal non-cancerous tissues had been taken from patients with dysphagia, endoscopically normal or margins of carcinomas. Specimen type of all of the samples had been biopsies from esophageal tissues, as formalin fixed and paraffin embedded (FFPE) tissue blocks.+/GP6+ and MY09/MY11), and E6 and E7 gene sequences. The laboratory methods used for detection of HPV genotypes were genotype specific PCR primers (E6/E7), sequencing of the PCR product, Real-time fluorescence detection (FRT) kit, restriction fragment length polymorphism (RFLP), and INNO-LiPA HPV genotyping kit  in both groups . Out of 1444 samples, 334 (23.13%) patients were positive for HPV. In another word, HPV was positive in 269 (25.32%) of the 1062 ESCC cases and in 65 (17.01%) of 382 controls . Accordih groups .P=0.001). According to regions of Iran, the maximum prevalence of HPV infection was 0.378  in North of Iran , as high incidence region  (P<0.05) and with the age of patients (P<0.05). The difference in HPV-16 prevalence in different regions of Iran was not statistically significant .The pooled prevalence of HPV-16 was estimated 0.121 (95%CI: 0.087–0.183) by using the random effect model ( =78.25) . There wP<0.001, I2=58.368) (P=0.07).The pooled prevalence of HPV-18 was estimated at 0.045  by using the random effect model (=58.368) . In addi2=75.55 and P =0.001, we used the random-effects model. The estimated pooled odds ratio (OR) was 1.988 , which indicates that the exposure ratio in ESCC cases was approximately two-fold more than the controls. However, this ratio was not statistically significant with respect to the confidence interval (P=0.08)  .Overall, 8 studies had reported the histopathological degree of ESCC in the patients, including 141 well differentiated, 182 moderately differentiated, 91 poorly differentiated, and 33 not differentiated. The histopathological degree of ESCC cases was not statistically significant with respect to study regions, years of publication and ages of patients.We investigated the prevalence and relation of HPV infection with esophageal squamous cell carcinoma (ESCC) in Iran. Overall, 14 studies were eligible including 1444 samples (1062 ESCC cases and 382 controls). Out of 1444 samples, 334 (23.13%) patients were positive for HPV. The total prevalence of HPV in both groups was estimated 0.256 . HPV-16 was the most frequent type with a pooled prevalence of 0.121 (65%CI: 0.087–0.183). The frequency of HPV in ESCC cases and non-cancerous controls were 318 (25.32%) and 65 (17.01%), respectively. In six case-control studies, the risk or odds ratio (OR) was estimated at 1.988 (95% CI: 0.716–4.438). The maximum prevalence of HPV infection was in North of Iran, with a higher distribution of esophageal cancer (EC). This study provides comprehensive evidence of HPV prevalence and association of HPV with ESCC in Iran.In a meta-analysis including 17 studies, the prevalence of HPV in Iranian patients with gastrointestinal cancers was 16.4% (95% CI: 10.4–24.9). Considering all HPV genotypes, the OR of gastrointestinal cancers in positive cases was 3.03 (95%CI: 1.42–6.45), but in HPV-16 positive patients OR was 3.62 (95% CI: 1.43–4.82) . The reaA systematic review and meta-analysis was conducted on the association of HPV-16 and HPV-18 with EC worldwide. In 33 randomized studies HPV infection rate in the EC group was 46.5%, while HPV infection in the control group was 26.2%, . There were statistical differences in HPV detection methods, including PCR, immunohistochemistry (IHC) and in situ hybridization (ISH). The merged OR was 1.61 (95% CI: 1.33–1.95) in the PCR detection group. The authors concluded that HPV infection closely associated with EC . In sensitivity analysis, the estimates for OR ranged from 5.92  to 6.97 . HPV-16 infection may be a risk factor for the EC among Chinese population .Overall, 3429 EC cases were evaluated from 26 eligible studies in China. The pooled estimate of HPV-16 prevalence was 0.381 . The prevalence varied by geographical regions, publication year, HPV detection method and specimen type. A relatively high level of HPV-16 prevalence was in the EC among Chinese population .A meta-analysis was conducted worldwide, including 124 studies with 13 832 ESCC cases. The estimated prevalence of HPV in ESCC cases was 0.277  by PCR; 0.243  by ISH; 0.304  by IHC; 0.322  by L1 serology; and 0.176  by Southern blot assay. The highest HPV prevalence was occurred in Africa and Asia, especially in China. Case-control studies should be done on the quantifying of HPV in ESCC cases and detection the association between HPV and the incidence of ESCC in large populations for a dipper understanding of the etiologic role of HPV on ESCC , pooled HPV prevalence in ESCC cases was 22.2% . HPV-16 was the most frequent type with a pooled prevalence of 11.4% (95% CI: 8.2%–15.7%). HPV prevalence in EA cases was 35.0%  and prevalence of HPV-16 was 11.4% (95% CI: 8.2%–15.7%). The association between HPV infection and ESCC was significant with a pooled OR of 3.32 . With respect to HPV-16, the OR of the association was 3.52 . HPV infection was associated with an increased risk of ESCC. However, due to the heterogeneity of studies and weaker association in comparison to cervical and laryngeal cancer, more studies are needed to clarify the relation of HPV and ESCC .A meta-analysis was performed on 132 studies about the relation of HPV and ESCC. An increased risk of ESCC in patients with HPV was found . The prevalence of HPV in ESCC cases was 24.8%. The risk of ESCC associated with HPV-16 infection was high . This risk of association was higher in Asia , particularly China . The authors concluded that an increased infection of HPV occurred in ESCC cases .In a meta-analysis including 5755 ESCC cases from 68 studies, 11.67%  of ESCC cases had HPV-16 and 1.82%  had HPV-18. In 10 case-control studies a significant increase in ESCC risk was observed for HPV-16, summary OR was 3.55 , but no significant increase for HPV-18, summary OR was 1.25 . HPV-16 and HPV-18 can be detected in ESCC cases and HPV-16, but not HPV-18, was associated with the risk of ESCC .P=0.440) from the different regions. Wide variability in HPV rates in ESCC cases is not due to the detection methods but is due to the geographic region of the study. ESCC might have different etiologies in low-incidence and high-incidence regions, and HPV was an important role in the latter regions  were positive for HPV, with an effect size of 0.29 (95% CI 0.251–0.31) using random effects model. A significant heterogeneity observed between the studies . From all ESCC cases, 426 (35%) were positive for HPV. The pooled OR for the association of HPV and ESCC was estimated at 3.04 . The effect of individual studies on the pooled estimation was non-significant. In countries with lower to medium ESCC incidence the relationship was stronger  than regions with high ESCC incidence . It was concluded that hesitancy about the role of HPV in ESCC was due to the low number of well-designed studies. In addition, HPV infection increases the risk of ESCC 3-fold and vaccination could prevent ESCC in high incidence countries (P=0.023) and HPV-6 . No significant associations were observed between ESCC and antibodies to E7 of the HPV types. In addition, significant associations was between ESCC and antibodies to L1 capsid protein of HPV-33 , HPV-6  and HPV-11 . There was limited serological evidence of an association between ESCC and HPV in their population  and/or the HPV early proteins (E6 and/or E7). Statistically significant associations were observed between ESCC and antibodies to E6 of HPV-16  in healthy individuals. Virus type in five of them was HPV-18. Moreover, HPV-6 and HPV-66 types were detected in two cases. Relation of oral HPV positivity to demographic data and risk factors was not statistically significant .Power of association between HPV and esophageal cancer has not been as strong as detected in cervical and laryngeal cancer . This maIn comparison, the results of HPV prevalence and its association with ESCC in the present study were somewhat similar to some previous studies. The differences of results of in the present study may be due to geographical region, environmental factors, differences of the population , research design, sample size, type of specimen, statistical analysis, and heterogeneity of included studies.High-risk human papillomaviruses were observed in ESCC tissues and controls from different regions of Iran. The odds ratio indicates that the HPV in ESCC cases was approximately two-fold more than the controls. With respect to the defined oncogenic role of HPV in some cancers such as cervical cancers, the causality of this virus in ESCC needs more case-control studies in other populations with larger sample size.Ethical issues  have been completely observed by the authors.


Human papillomavirus (HPV) positive head and neck cancer displayed specific transcription landscape but the underlying molecular mechanisms are not fully determined. Here, we interestingly found that HPV infection could globally elongate the 3’-untranslated regions (3’UTRs) in the majority of alternative polyadenylation (APA)-containing genes. Counterintuitively, the 3’UTR elongation does not affect their resident gene expression. Rather, they significantly increase the number of binding sites for RNA-binding proteins (RBPs) and subsequently upregulate a group of oncogenic genes by absorbing RBPs. A significant fraction of HPV affected genes are regulated through such mechanism that is 3’UTR-mediated recruitment of RBPs. As an example, we observed that HPV infection increases the length of 3’UTR of RBM25 transcript and hence recruits much more RNA binding protein including FUS and DGCR8. Consequently, in the absence of FUS and DGCR8 regulation, PD-1 was rescued and up-regulated after HPV infection. Taken together, our findings not only suggest a novel paradigm of how oncogenic viruses shape tumor transcriptome by modifying the 3’UTR, but also present a previously unrecognized layer of APA—RBP interplay in this molecular hierarchy. Modification of the pool of RBP-binding motif might expand our understandings into virus-associated carcinogenesis. Cancer is a group of diseases involving abnormal and aggressive cell growth accompanied by loss of tissue-specific function. It has already become one of the most challenging diseases that affect health globally, but its etiology is still not fully understood. Several known risk factors such as viral infection, tobacco use, obesity, and excessive drinking of alcohol can significantly increase the incidence of a subtype of cancer –4. In paIn general, there are seven known human oncogenic viruses, including human papillomavirus (HPV), hepatitis B virus (HBV), hepatitis C virus (HCV), human T- lymphotropic virus 1 (HTLV-1), Epstein–Barr virus (EBV), Kaposi sarcoma- associated herpesvirus (KSHV), and Merkel cell polyomavirus (MCPyV) . HPV is Alternative polyadenylation (APA) was shown to regulate the inclusion of sequences into the 3’-untranslated regions (3’UTRs) and thus involved in multiple biological processes by affecting the stability, localization, and half-life of the mRNAs . EvidencTo date, freshly published computational tools and datasets  make it It remains an open question of how HPV impacts host cells and induces oncogenic changes. Recent findings have suggested the biological significance of miRNAs in HPV positive tumors ,20, wherTo test our hypothesis, we first compute the PDUI for APAome in both HPV+ and HPV- HNSC samples. PDUI is a widely-accepted quantifying unit for evaluating APA level by using RNA-seq data  . RAID isTo further validate the APA—RBP—paired gene axis, we next explore whether the paired genes are in an RBP-dependent manner. We divide the interactome into two groups: RBP+ and RBP- groups, which are defined as higher or lower RBP-binding confidence level . The RBP+ group means APA regulates paired genes via more intermediate RBPs in a high confidence level. In contrast, RBP- group represents a weaker bridge between 3’UTR and paired genes. The Y-axis marks the -log  of differential expression between HPV+ and HPV- samples. The bigger the Y-axis value is, the group harbors a more HPV-specific trend. Firstly, among the APA negative groups, no significant difference of HPV-specific-trend is observed between RBP+ and RBP- sets . On the contrary, in the APA+RBP+ group, the -log  of differential expression are upregulated significantly compared with the other three groups . This reNext, to better quantify the functional impact of the global APA-changed paired genes, we monitor the associated biological processes. With a focus on the hub 3’UL genes, we limit the cutoff number of intermediate RBPs to ≥ 15. Interestingly, the cell cycle is the top ranking term, which is strongly in consistency with our previous understandings into HPV+ tumor ,27 Figu. Further30. Yet, very little is known about the underlying mechanism. Therefore, we asked whether HPV infection affects PD-1, which is a key inhibitory checkpoint of CD8 T cells. Interestingly, in accordance with previous reports [To further confirm the identified paradigm that HPV shapes host cells by using APA—RBP—paired gene axis, we next focus on individual key molecules to examine the paradigm . A recen reports , we confTo further determine whether HPV regulates PD-1 in the 3’UL dependent manner, we focus our analysis on the RNA-seq data. HPV infection can robustly increase the APA level of RBM25 and GTF3C3 . WithoutTo further prove our hypothesis that 3’UTR lengthening affects gene expression via RBP, we focus on the cell cycle process of cancer cells which is the hallmark of HPV infection ,29. ThouTo further gain insights into associations between HPV and cell cycle regulator E2F1, we re-check the differential APA profile. Surprisingly, among the APAome, E2F1 undergo 3’UTR lengthening  indicatiViral infection greatly contributes to the global cancer burden, but how oncogenic virus transforms normal cells to cancerous cells is still poorly understood. Viral infection widely affects gene expression and several common virus-targeted pathways have been identified. For example, virus profoundly altered the miRNA profile and activate oncogenic processes . HoweverThe 3’UTRs of eukaryotic mRNA is generated through endonucleolytic cleavage at poly(A) site and subsequently polyadenylation by the poly(A) polymerases . The choIncreasing evidence indicates that APA is extensively used and is an important way to regulate gene expression –44. The Pan-cancer analysis across 7 cancers including 358 tumor/normal pairs reveals that most APA genes (91%) in tumors have shorter 3′ UTRs. Besides these global features of APA events in cancer, several specific APA regulated genes in different cancer have also been investigated. For example, in hepatocellular carcinoma, downregulation of CFIm25 subunit of cleavage factor results in high expression of PSMB2 and CXXC5 by increasing the usage of the proximal polyadenylation site . In pancIn a nutshell, by comparing the APA events between HPV infected or non-infected cancers, we found HPV-induced features of APA. Through elongating the 3’UTRs, HPV indirectly changes the RBP targets for their survival and cell transformation. Our work not only presents a novel paradigm of how oncogenic viruses shape tumor transcriptome by modifying the 3’UTR, but also highlight a previously unrecognized layer of APA—RBP interplay in this molecular hierarchy. Modification of the pool of RBP-binding motif might provide new insight to understand virus-associated carcinogenesis.All the RNA-seq data were fetched from The Cancer Genome Atlas. We retrieved the level 3 transcriptome raw counts and FPKM profile of head and neck squamous carcinoma samples. The HPV positive/negative statuses were defined by the p16 testing results. Samples without HPV status and their RNA-seq data were excluded for computation. Non-tumor samples were excluded. In all, 111 patient samples were included in the analysis, including 73 HPV negative samples and 38 HPV positive samples. The detailed patient clinical information can be seen in https://github.com/ZhengXia/DaPars). APAome refers to all APA events detected by DaPars. To infer the proximal polyadenylation sites, 3’UTR annotation was generated based on UCSC hg19 reference (python DaPars_Extract_Anno.py -b gene.bed.txt -s symbol.txt -o 3UTR.bed). The Percentage of Distal polyA site Usage Indexes (PDUIs) was computed for all transcripts (python DaPars_main.py my_configure_file.txt). The PDUI score ranges from 0 to 1, which indicate from full shortening to full lengthening of 3’UTR. The larger PDUI indicates the longer 3’UTR that each transcript has. We used the Wilcoxon test for differential APA analysis which has been used before [The Cancer 3’UTR Atlas yields the characterization of APAome based on RNA-seq by using DaPars ,52  and CLUEGO.Gene ontology enrichment and pathway enrichment annotation were computed through Molecular Signature Database (Patients were split according to the viral status and the longest survival time was set as two years. The P-value for survival analysis was computed through the log-rank test. Principle component analysis was analyzed based on ggfortify package in R. APA events with null values were discarded for principal component analysis urged by ggfortify package.Supplementary FiguresSupplementary Table


The Adaptive Boosting (AdaBoost) algorithm is a widely used ensemble learning framework, and it can get good classification results on general datasets. However, it is challenging to apply the AdaBoost algorithm directly to imbalanced data since it is designed mainly for processing misclassified samples rather than samples of minority classes. To better process imbalanced data, this paper introduces the indicator Area Under Curve (AUC) which can reflect the comprehensive performance of the model, and proposes an improved AdaBoost algorithm based on AUC (AdaBoost-A) which improves the error calculation performance of the AdaBoost algorithm by comprehensively considering the effects of misclassification probability and AUC. To prevent redundant or useless weak classifiers the traditional AdaBoost algorithm generated from consuming too much system resources, this paper proposes an ensemble algorithm, PSOPD-AdaBoost-A, which can re-initialize parameters to avoid falling into local optimum, and optimize the coefficients of AdaBoost weak classifiers. Experiment results show that the proposed algorithm is effective for processing imbalanced data, especially the data with relatively high imbalances. Since imbalanced data can be found in any area, effective classification of imbalanced data has become critical for many applications. The classification results of imbalanced data generated by existing classification algorithms are usually significantly affected by the majority class, resulting in low accuracy in classification of the minority class. For example, the sensor network can accurately achieve target recognition under the assumption of data distribution equilibrium. However, in practical applications, the filed environment is complex and variable, and the difficulty of obtaining samples is different, which results in imbalanced data. It is easy to ignore samples of minority class in this case, resulting in incorrect classification. In the intrusion alarm application, misclassification of samples of minority class means false alarm of system, which will cause very serious consequences.Existing approaches processing imbalanced data can be generally divided into two categories ,2. The fMany approaches have been proposed to improve the performance of AdaBoost. Li et al.  proposedIn this paper, we propose AdaBoost-A, an improved AdaBoost algorithm based on AUC. The AdaBoost-A redefines the error calculation formula by introducing the AUC index into the error calculation of the weak classifier. The AUC can evaluate the performance of a classifier, and reflect the effects of imbalanced data on the classifier. As a result, the proposed AdaBoost algorithm can focus more on samples of minority class. In addition, the AdaBoost-A algorithm generates a set of weak classifiers to build a strong classifier, and the improved particle swarm optimization algorithm based on population diversity is used to further optimize the weight of the classifiers, thus decreasing the weight of redundant and useless classifiers and avoiding waste of system resources and time overhead.The remainder of this paper is organized as follows. In AdaBoost (Adaptive Boosting) is an adaptive enhancement technique. It is a typical ensemble algorithm which improves classification performance by combining multiple weak classifiers into one strong classifier. In the beginning, all the samples are assigned the same weight. During the iteration, the weights of samples vary with the coefficients of weak classifiers, and the coefficients of the classifiers are calculated by the error. As a result, the AdaBoost algorithm can increase the weight of the misclassified samples and decrease the weight of the correctly classified samples. In the next iteration, the classifier will focus the misclassified samples more. Finally, all the generated weak classifiers are merged using linear combination to form a strong classifier. The steps of the AdaBoost algorithm  are as fInput:Training data set Output: Final classifier Initialize the weight distribution of the training samples following Equation (1).Following Equation (2), get the weak classifier based on weight distribution Calculate the classification error rate of Calculate the coefficient of Update the weight distribution of the training samples following Equations (5)–(7).For Build a linear combination of basic classifiers and get the final classifier The advantages of the AdaBoost algorithm are summarized as follows. (1) The AdaBoost algorithm can use various weak classifiers without filtering features. In addition, it delivers high execution efficiency, and can avoid overfitting issues. (2) The AdaBoost algorithm trains the weak classifiers without knowing the prior knowledge. The synthetic strong classifier can significantly improve the classification accuracy, and it is suitable for classification of most types of data. (3) The training of rough weak classifiers is much easier than training of the accurate strong classifiers. It trains multiple weak classifiers to form a strong classifier with better classification performance.PSO was proposed by James Kenney and Russ Eberhart in 1995 . The algThe PSO algorithm considers each solution as a bird, called a particle. Each particle has an adaptive value that represents the current state of its own solution. In each iteration, each particle adjusts its moving direction and velocity based on the global optimal solution and the optimal solution found by the particle itself, and gradually approaches the optimal particle.The basic principle of the standard particle swarm algorithm is as follows .Suppose that there are As Equation (13) shows, the current best position As Equation (14) shows, the current best location The position and velocity of particle particle .It is possible to quickly approximate the optimal solution and achieve effective optimization of parameters.It is suitable for searching within the scope of continuity and solving the maximum and minimum problems of continuous functions.It is easy to implement with low complexity and requires a small number of parameters.It is easy to fall into local optimum.Characteristics of PSO algorithm can be summarized as :It is poConfusion matrix is the common method to reflect performance of classification model. Taking a two-class model as an example, the confusion matrix of this model is calculated as shown in Based on the confusion matrix, the Accuracy, Precision, Recall and F1-Measure are defined as follows:The TP, FP, TN, and FN measures can be collected to construct a plot, which is a Receiver Operating Characteristic (ROC) curve, which the true positive rate (TPR) as the ordinate and the false positive rate (FPR) as the abscissa. The calculation formula TPR and FPR are shown in Equation (21).The value of AUC is the area under the ROC curve. Suppose AUC is a comprehensive evaluation of classification models, which can provide more useful information than accuracy measurement.Although the AdaBoost algorithm can be directly applied to imbalanced data, the ensemble algorithm pays more attention to the misclassified samples, rather than samples of minority class. According to the error calculation formula of the weak classifier of AdaBoost, the error is only related to the weight and the number of misclassified samples. There is no additional processing for the misclassified samples of minority class, so the AdaBoost ensemble algorithm is not well suited for processing imbalanced data . To solvAlthough the AdaBoost algorithm can combine multiple weak classifiers into one strong classifier, the coefficients of the weak classifiers are determined in the iteration process. These coefficients cannot be changed later, so it is inevitable to generate redundant or useless weak classifiers that have large weights. This can significantly affect the readability of the classifiers and increase system overhead. To overcome these shortcomings, our approach uses the PSO algorithm to optimize the weights of the weak classifiers of AdaBoost-A. This algorithm assigns large weights to the weak classifiers with high accuracy, and small weights to the redundant or useless weak classifiers, further improving the accuracy and readability of AdaBoost classifier. PSO is an optimization algorithm with a small number of parameters and fast convergence, but it is easy to fall into local optimum . TherefoUse the AdaBoost-A algorithm to generate several (Set the population size to Use the position component of each particle as the weight coefficient of the weak classifier of AdaBoost-A. As Equation (28) shows, the error rate For each particle, the fitness value generated by each iteration is compared with the fitness value of the optimal position passed by the particle. If the fitness value is greater than the fitness value of the optimal position, the current position is taken as the optimal location passed by the particle, recorded as For each particle, the fitness value generated by each iteration is compared with the fitness value of the optimal position passed by all particles. If the fitness value is greater than the fitness value of the optimal position of all particles, the current position is taken as the global optimal location, recorded as Update the position and velocity of the particle in the following iteration based on the Equations (15) and (16).When the maximum number of iterations is reached or the error is small enough, the iteration stops. Otherwise, check the number of consecutive times that the optimal particle remains unchanged. If it reaches the threshold (10 is used in our configuration), the optimal particle is retained, and the position and velocity of other particles are reinitialized. If it is less the threshold, no action is performed. Then continue to execute steps 4–6.The PSOPD-AdaBoost-A ensemble algorithm is described as follows:We evaluate the proposed algorithm using the Vehicle, Horse Colic, Ionosphere and Statlog imbalanced datasets from UCI repository and KC1, JM1, PC3, PC5, CM1 imbalanced datasets from NASA. In addition, the weak classifiers are generated by Decision-Stump. The Vehicle dataset is split into training and test sets at a ratio of 7:3. The standard AdaBoost algorithm is used to classify the samples in the training set. As the number of weak classifiers increases, the growth trend of AUC is shown in To eliminate the impact of data division and guarantee valid results, the 10-fold CV is employed to evaluate the classification performance. The detailed comparison results for the AdaBoost-A algorithm and the AdaBoost algorithm on Vehicle dataset in terms of the error and AUC are showed through box plots in The KC1 dataset is split into training and test sets at a ratio of 7:3. The standard AdaBoost algorithm is used to classify the samples in the training set. As the number of weak classifiers increases, the growth trend of AUC is shown in The detailed comparison results of the 10-fold CV for the AdaBoost-A algorithm and the AdaBoost algorithm on KC1 dataset in terms of the error and AUC are showed through box plots in Through the above experiments, it is proved that the proposed AdaBoost-A algorithm is more effective than AdaBoost algorithm.The coefficients of AdaBoost-A weak classifiers are optimized by the improved PSO based on population diversity and the standard PSO on the five imbalanced datasets, respectively. We compare classification performance of them by performing 5-fold CV. The detailed classification results of the AdaBoost, PSO-AdaBoost-A, and PSOPD-AdaBoost-A algorithms based on the average of 100 runs are showed in As shown in To solve the imbalance problem, researchers have proposed many approaches to improve the ensemble algorithms, but most of the improved methods are still sensitive to the relatively high imbalance rate. Next, we compare classification performance of our PSOPD-AdaBoost-A approach and boosting algorithms including G-AdaBoost based on genetic algorithm , B-AdaBoThe mean of Accuracy, Precision, Recall, F1, AUC, and Error of the four datasets are summarized in Through the above comparative experiments, it is proved that the PSOPD-AdaBoost-A ensemble algorithm is more effective in processing imbalanced data compared to many improved algorithms.Traditional AdaBoost algorithm focuses on the misclassified samples instead of the samples of minority class. In this paper, we propose an improved AdaBoost algorithm (AdaBoost-A). Since the AUC can effectively reflect the performance of the classifier, we introduce the AUC into error calculation, making the AdaBoost focus more on the classification accuracy of the minority. Furthermore, the AdaBoost algorithm may generate redundant or useless weak classifiers, significantly affecting the readability of the classifier. We propose an ensemble algorithm, PSOPD-AdaBoost-A, which can further optimize the weight of the weak classifiers. Experimental results show that the AdaBoost-A and PSOPD-AdaBoost-A ensemble algorithms can effectively classifying imbalanced datasets, Vehicle, KC1, Horse Colic, Ionosphere, JM1, and Statlog. Next, we compare the imbalanced data classification performance of PSOPD-AdaBoost-A with ensemble algorithms including G-AdaBoost, B-AdaBoost, D-AdaBoost, Random Forest, and Extra Trees, sampling method including Smote, and four datasets with relatively high imbalance rate, Vehicle, PC3, PC5, and CM1 are used in the comparison. The results show that the PSOPD-AdaBoost-A ensemble algorithm is effective in processing data with relatively high imbalance rate compared to other improved algorithms. Our future work is dedicated to applying the proposed algorithm to the field of sensors, accurately achieving classification of targets by processing imbalanced data acquired by sensors.


Oral cancer associated with high risk (HPV-HR) human papilloma virus (HPV) has been increasing. HPV-HR has been associated with epithelial dysplasia, however, little information exists on its frequency in epithelial hyperplasia lesions. The aim of this study is to compare HPV genotypes in dysplastic and hyperplastic lesions of oral cavity. Two hundred and fifty oral lesions: 131 dysplasia and 119 hyperplasia from two regions of Colombia were evaluated. One hundred seventy-four coming from urban area and 104 from a high risk population to oral cancer from a rural area. HPV was identified by qPCR and Twenty-four HPVs genotypes were evaluated by Luminex® technology. Logistic regressions were performed to establish the associations between HPV infections with oral dysplasia. Twenty-eight percent (70/250) of the samples were positives for any HPV and HPV-HRs were more frequently than low risk HPVs. HPV-16 was the most detected genotype (16%) followed by HPV-31, 53, 18 and 45. HPV, HPV-HRs and HPV-16 were only associated with dysplasia in urban area; OR 3.28 (CI 95% 1.49-7.17), OR 7.94 (CI 95% 2.97-21.2) and OR 5.90 (CI 95% 2.05-17). Individuals in rural area showed more HPV and HPV-HRs infection in hyperplasic lesions than urban population. The majority of HPV+ lesions had multi-type of HPV (52/70) and the urban individuals showed more genotypes than rural population.  HPV-.HRs are frequently found in hyperplastic and dysplastic epithelial lesions. HPV-HRs and HPV-16 were associated with dysplasia in urban population. Rural high risk population and urban population differ in the frequency and variety of HPV genotypes. Key words:Human papilloma virus, epithelial dysplasia, epithelial hyperplasia, HPV-genotypes. While the incidence of cervical cancer has been decreasing in industrialized countries, the incidence of HPV in oral cavity and oropharynx cancers has been increasing over the past 20 years ,2. An inHPV infection is considered a sexually transmitted disease, and some sexual practices as lifetime coital sex partnership numbers and the number of oral sex partners has been associated with HPV transmission to the oral mucosa -9 and maet al., . These lesions refer to an altered epithelium with a higher probability of progression to squamous cell carcinoma and these changes involve epithelial dysplasia . Howeveret al.,  proposedet al., ,16.Based on their potential oncogenic activity, HPV subtypes have been divided into high-risk (HPV-HRs) and low risk (HPV-LRs) viruses. HPV-HR are associated with the development of cancer and are termed oncogenic viral types ,18. HPV-More of 100 different genotypes of HPV has been recognized and 15 have been classified as HPV-HRs ,24. ReceThe purpose of this study is to identify the main genotypes of HPV in oral mucosal lesions according to histological changes by comparing lesions with OPMD-based dysplasia with those showing hyperplastic changes without dysplastic.Material and methods- Type of studyA cross sectional study was realized comparing the HPV genotypes in oral lesions with dysplasia and epithelial hyperplasic histologic diagnosis.- PopulationTwo hundred and fifty oral mucosal lesions of individuals diagnosed in different services associated with the universities participants of two geographic regions of Colombia (Bogotá and the Caribbean region) were evaluated. One hundred thirtyone [131] lesions with dysplasia and 119 lesions with histologic diagnosis of hyperplasia without dysplasia were analyzed to identify 24 HPV genotypes by the Luminex® technique. One hundred twenty-three samples come from Bogota and 127 come from Caribbean Region. One hundred forty-six [146] individuals were evaluated from urban areas of the two geographic regions in retrospective and prospective evaluation and the samples were obtained from 2010 to 2018. A subset of samples [104] obtained in a specific high risk to oral cancer population associated with the habit of reverse smoking in rural area of Caribbean region (Sucre-Department) obtained in 2004  also werThe study was approved by the Ethics Committee of the School of Dentistry of Universidad El Bosque (Act. No. 012-2013). All samples evaluated were obtained with informed consent.- Clinical and socio-demographic dataSocio-demographic data such as age (≤ 45 age/ >45 years), gender , region (Bogotá/Caribbean), area , date of diagnosis (≤ 5 years/ 5-10years/ >10 years) were obtained in all samples. Other data such as cigarette and alcohol consumption could not be obtained for all samples because many were obtained from seizures of oral pathology.- Selection and exclusion criteriaClinical diagnoses: Oral lesions not associated with oral infections  were included in this study. Lesions from different locations of the oral cavity were included, except for lesions of the oropharynx and soft palate or lesions of floor of the mouth including floor of the tongue. White, red, pigmented and lesions without color change such macules, papules, plaques, nodules, clinical hyperplasia, ulcers, erosions and blisters, were included for histological analysis. The lesions were included if in the histopathological analysis they showed a diagnosis of hyperplasia or epithelial dysplasia.Histologic diagnoses: expert pathologists evaluated all samples in each region. The samples were classified into 1) with the presence of dysplasia 2) with the presence of epithelial hyperplasia without dysplasia. In dysplasia, the cells look abnormal: there are cells of differing sizes, misshapen cells, intensely pigmented cells and an uncommon number of cells presently dividing, but they are not cancer. In hyperplasia, there is an increase in the number of cells in an organ or tissue that appear normal under a microscope. The basal and para basal hyperplasia were excluded.- DNA isolation from paraffin embedded tissue Aamp® DNA FFPE Tissue kit . Briefly, the paraffin was removed by vortexing and 10 minutes incubation with 1.2 mL xylene, followed by two washes with pure (200 proof) ethanol. The air-dried pellet was then incubated with 20 μL proteinase K and 180 μL ATL lysis buffer for 16 hours in a heat block at 56°C. The lysed emulsion was further purified with the DNeasy spin-column kit. DNA was finally recovered in a single elution step with 100 μL AE solution from the kit.To minimize the potential for PCR contamination, the histotechnologists were instructed to wear gloves when handling blocks and to clean the microtome and the area around the cutting station before beginning work, and to use a new disposable microtome blade for each block. Six serial 5-μm sections were cut from each block. The sections were transferred directly from the microtome blade into a 1,5mL tube, yielding two tubes per block. Total DNA was extracted from the replicate tubes using the QI- Quality Assessment of DNA and HPV identificationQuality of DNA was confirmed by PCR with primers PC03/PC04, which amplify a 110 bp fragment of the ß-globin gene. The PCR products were visualized by gel electrophoresis on 1% agarose gels stained with SYBR Safe to identify the amplified 110pb band. qRT-PCR was performed for detection of HPV in samples using GP5+/GP6+ consensus primers with Kappa SYBR Green mastermix kit (Kapa Biosystems®) and CFX96 Bio-Rad real-time thermal cycler . Briefly, the amplification was performed in 25 μl reaction mix containing 0,2µM each of GP5+ and GP6+ primers and 30-50ng of genomic DNA in 5 ul of test volume. The amplification ramp included first step for 3 min at 95°C for initial denaturation, followed by denaturation cycle of 20 secs at 95°C, an annealing cycle of 15 secs at 48°C and an elongation and readout cycle of 30 secs at 72°C for 45 cycles. Genomic DNA from HPV positive cells lines CaSki, SiHa and HeLa was used as positive controls. The specificity of PCR product was verified by a dissociation curve analysis.- Multiplex HPV genotyping with Luminex® TechnologyThe sample DNA extracted from paraffin embedded tissue was subjected to PCR amplification, using sets of biotinylated BGP5+/BGP6+ primers contained in the kit. Additionally, a pair of primers for the amplification of a ß-globin gene fragment were added to the PCR as a control. PCR products were added to the bead mix containing 26 distinct bead populations coupled to 24 HPV, one ß-globin and one Hybridization Control specific oligonucleotide probe. The ß-globin control serves as quality control for genomic DNA in the PCR. After thermal denaturation and hybridization of target sequences to the bead-bound probes, labeling of the hybridized biotinylated PCR products was achieved by R-Phycoerythrin labeled Streptavidin (reporter fluorescence). The beads were analyzed in a Luminex 100 reader (Luminex Corp.), which uses two lasers, one that recognizes the bead set by the internal bead color and another to quantify the reporter fluorescence on the bead. Based on the detection of specific HPV and ß-globin PCR products and their combination, the following evaluation scheme should be applied  and specificity of 78.3% (624/797). The results were expressed in median fluorescence intensities (MIF) of ≥100 beads per sample.- Statistical analysis Descriptive analyses of frequency distribution were carried out for all variables. Bivariate analysis was performed by chi-square/Fisher tests to establish associations of the HPV, HPV-HRs, HPV-16, and HPV-18 with oral dysplasia compared with hyperplasia. All variables of HPV infection which showed a significance level <0.10 in the bivariate analysis were included in a logistical regression analysis to establish the OR with confidence intervals of 95% adjusted to age and gender (Model 1) or adjusted to age, gender, region and area  (Model 2). For all logistic models the goodness of fit tests for logistic regression (Hosmer-Lemeshow test) were performed. The models were compared with using the likelihood ratio chi-square and the Bayesian information criterion (BIC). A multiple correspondence analysis was performed to establish the correlation between the different genotypes of HPV in multiple infections. All data analysis was undertaken using Stata .- Characteristics of the samplesThe samples were mostly lip, palate and oral mucosa and with less frequency of tongue and gingiva. One hundred and thirty-one had a histological diagnosis of dysplasia and 119 were lesions with hyperplasia. The lesions most frequently evaluated for both types of histological diagnosis were white lesions, although these were more frequent in lesions with dysplasia (54.2% vs. 32.7%) and most were plaque lesions. The red lesions were also frequent but the pigmented lesions were the least frequent. Leukoplakia was the most frequent diagnosis in both histopathological diagnosis but this was more frequent in dysplasia, however, only half of the lesions had a presumptive clinical diagnosis .- Characteristic of populationThe socio demographic and clinic characteristics of the lesions evaluated are shown in - HPV Frequencyp=0.75). HPV-HRs, HPV-16 and HPV-18 were also more frequently identified in dysplasia lesions (p>0.05). (Data not shown).70/250 (28%) of the samples were positives for any HPV evaluate by qPCR. The samples HPV+ were most frequently in samples with dysplasia than hyperplasia (32.8 vs. 22.7%) but the differences were not significant  were HPV-HRs +. HPV-16 was detected in 41/250 (16.4%), HPV-31 in 21/250 (8.4%), HPV-18, in 15/250 (6%), HPV-45 in 9/250 (3.6%), and HPV-33, HPV-35 and HPV-59, in less than 3% of the HPV+ samples. The HPV-LRs more frequently were HPV-11 in 9/250 (3.6%) and HPV-6 in 8/250 (3.2%). In only three cases the individuals were infected with one genotype, in the in the majority were multiple infections with other HPV-HRs viruses. Fifty-two 52/250 (20.8%) lesions showed infections by multiple HPV genotypes. Twenty-two/250 (8.8%) had infection by two genotypes (4.2% for hyperplasia vs. 12.98% for dysplasia) followed by 5 or more genotypes 11/250 (2.52% for hyperplasia vs. 6.11% for dysplasia). A lower frequency was observed for infections by 3 and 4 genotypes simultaneously (3.2 for hyperplasia vs. 4% for dysplasia). A multiple correspondence analysis is observed in Fig. - HPV Genotypes in samples with dysplasia and hyperplasiaHPVs-HR were more frequently in dysplastic samples although they were also detected in hyperplasia. HPV-55 and HPV-66 were exclusively detected in samples of dysplasia, HPV-42 y HPV-52 only were detected in hyperplasia. The HPV-LRs more frequently in hyperplasia were HPV-6, HPV-11 Fig. .- Association of VPH with dysplastic lesionsIn - HPV Genotypes in samples with dysplasia and hyperplasia in rural and urban samplesRural population showed more HPV-HRs genotypes in hyperplasic samples than urban samples Fig. ; HPV16, The impact of HPV has been investigated in oral cancer in the last decades and the association with OPSCC, and OSCC has been well established ,18. The Different studies have suggested that HPV infection is probably a potential etiological factor of OPMD . The terIn this study, although the presence of high-risk genotypes was more frequent in lesions with dysplasia in urban population, these differences were not observed in the rural samples when these were compared with lesions with hyperplasia. HPV prevalence varies according to different studies and these differences seem to be related with sample size, detection methods, geographic populations, disease types, and HPV genotypes and it could be related with the type of control group used .The prevalence of HPV in cancer-free individuals is low and has been reported in 7.7%; healthy patients had 1.4% of HPV-16 . HoweverIn rural area the frequency of HPV-HRs was much higher than the one observed in urban areas in epithelial hyperplasia. In rural population exist significant disparities in knowledge and awareness of HPV and the HPV vaccine compared to urban . In our The importance of HPV infection in oral epithelia in incipient lesions has focused on oral dysplasia. HPV-HR+ have been associated with dysplastic lesions when compared to normal mucous membranes . HoweverHPV-16 was the most important genotype of HPV in hyperplasic and dysplastic samples. HPV-16 has been the genotype most associated with OPSCC, OOPD, OSCC and OPMD followed by HPV-18 . In thisThe findings of this study do not support an association of HPV with oral epithelial dysplasia compared with epithelial hyperplasia because the results vary between geographical areas of the same country. The clinical significance of high-risk HPV loads in the malignant progression of oral potentially malignant disorders needs to be clarified. Recently, a retrospective cohort of premalignant oral lesions such oral lichen planus and dysplasia in Spain population evaluating HPV-DNA and p16INK4A expression followed by several years did not progress to invasive cancer . More stHPV, HPV-HRs and HPV-16 were more frequent in dysplasia lesions only in urban areas. HPV-16 is the most frequently genotype in the lesions evaluated but was associated with multi-type infection. HPV genotypes varies in rural and urban areas.- LimitationsOne limitation of this study was the lack of healthy oral tissue controls by ethics considerations. It was also not possible to obtain comparable samples from the population studied to obtain cytological samples to evaluate HPV. This study only compares hyperplasia and oral dysplasia samples. In this study it was not possible to establish associations of HPV with smoking habit because the information was not available. Other strong limitation of the study was the lack of clinical diagnosis in a great number of the cases.


Cervical cancer incidence varies around the world with the highest rates in Eastern Africa and the lowest rates in Western Asia. In Cyprus, a small Mediterranean island, cervical cancer incidence was 6.4 per 100,000 in 2013. HPV is an established risk factor for cervical cancer with HPV-16 and HPV-18 being the most common carcinogenic strains. Cervical cancer is preventable through primary (HPV vaccination) and secondary (Pap and HPV tests) prevention. These prevention methods should be promoted, however, in order to design a cancer prevention programme and the awareness and characteristics of populations should be investigated so that prevention programmes can be targeted specifically to them.In this work, we sought to investigate awareness of HPV and cervical cancer prevention among female healthcare workers in Cyprus. To achieve this, we conducted a 60-item survey among 200 healthcare professionals in randomly selected hospitals in two different cities within Cyprus.Our results revealed that nearly 10% of our participants reported not ever having had a Pap test. 88.5% of the healthcare workers knew about HPV and 86.5% reported that HPV is transmitted through sexual intercourse. 83.5% of the participants were willing to vaccinate themselves for cervical cancer prevention.Even though awareness and vaccination acceptance were relatively high, they are still not optimal for healthcare professionals who play an essential role in health promotion. We suggest the design of educational programmes to target this population and improve their knowledge so that they can promote cervical cancer prevention in their health practice. Globally, cervical cancer is the fourth most common cancer in women with 530,000 new cases diagnosed and more than 270,000 deaths every year . The incThe symptomology of the disease varies from having no symptoms to abnormal vaginal bleedings, unfamiliar vaginal discharges and pain during sexual intercourse . A corneCervical cancer is preventable. The availability of a cervical cytology test  and more recently HPV test has contributed to a decline in cervical cancer mortality. Furthermore, the development of a vaccine against various HPV strains is expected to further reduce cervical cancer incidence and mortality , 13. TheEven though vaccines against HPV have been shown to be effective in reducing the incidence of cervical cancer, awareness and knowledge about them still remains low. A recent study carried out in Nigeria showed that only 17.7% of the students had heard about human papilloma virus and only 14.4% were aware that HPV vaccines exist. Of the students who had heard of the HPV vaccine, only 46.2% knew that it was given to prevent cervical cancer . In addiEven more concerning is the lack of awareness and knowledge of HPV among healthcare providers who play a critical role in health promotion. A study in Singapore among 2,000 nurses reported that 81.9% of the nurses knew about the association of cervical cancer with multiple sexual partners, 78.2% knew about the association of cervical cancer with history of sexually transmitted diseases and 73.5% knew about the association of cervical cancer with HPV infection. However, the study revealed that the nurses had misconceptions about the efficacy, safety and indications of the vaccine. Only 54.6% of these nurses were aware of the preventive nature of the HPV vaccine and 20.5% had the misconception that the HPV vaccine is only indicated for women at high risk for cervical cancer . A similConsidering the misconceptions surrounding HPV and cervical cancer prevention in various populations, we assessed awareness of HPV and cervical cancer prevention in female healthcare workers in Cyprus. In addition, we investigated their attitudes towards HPV vaccination. Healthcare workers are at the frontline of health promotion and hence it is crucial that they are aware of various ways of cervical cancer prevention, especially with the availability of primary prevention. We hope our results can guide the design of cervical cancer prevention education programmes for healthcare professionals that would ultimately result in better education of the general public regarding this issue.N = Z2 PQ/D2; where N = required sample size, Z = 1.96 at confidence level of 95%, P = 0.15 = estimated proportion of women not adhering to cervical cancer screening guidelines from a similar study we conducted in Greece, D = margin of error at 5% (standard deviation of 0.05) and Q = 1–P . Almost three quarters (73%) of women reported having had Pap tests regularly for the past 5 years with a higher proportion of women over 30 years old (84%) compared to women ages 20–29 years (54%) . Multiple logistic regression revealed the positive association of cervical cancer screening frequency with age (older women had more frequent pap tests compared to younger women) and marital status (married women had more frequent pap tests compared to single women) (The percentage of participants that reported never having had a Pap test was 9.5. The main reasons recorded for not having the Pap test were negligence (42.1%), not experiencing symptoms (21%) and fear of the results (15.7%). Among the group that have done the Pap test, a significantly higher proportion of women (99%) older than 30 years had done the Pap test compared to women ages 20–29 years (74%) [e women) . Cervicap = 0.0185).We assessed general features of the health behaviour of the participants such as smoking, use of contraceptive pills and visits to the gynaecologist. The majority (81%) of participants reported being non-smokers and 16.5% reported being smokers. Among the smokers, 3% smoked for less than a year, 6.5% for 1–4 years, 3.5% for 5–10 years and 5% for more than 10 years. The percentage of women that reported visiting their gynaecologist once a year was 76.3%, while 9.8% reported never visiting the gynaecologist. The percentage of the participant women that reported not using contraceptive pills was 67. We found that a higher proportion of women taking oral contraceptive pills have done a Pap test (98.3%) compared to women not taking contraceptive pills (86.5%) (A large percentage (88.5%) of the participants reported that they know about the human papilloma virus and 86.5% selected sexual intercourse as a route of transmission of HPV (Nearly one-fifth (18.33%) of healthcare workers reported that they are not aware of the existence of an HPV vaccine. The questionnaire also included questions about the participants’ acceptance of the vaccine for themselves, their daughters and their sons. Interestingly, 79.47% of the participants would accept getting vaccinated to protect themselves from HPV infection and 83.5% would accept vaccination to prevent cervical cancer. The major reason reported for refusing to get vaccinated was ‘fear of side effects’ (55.12% participants chose that answer) . AcceptaOverall our study participants appeared to be attentive to their health as evidenced by the majority of them being non-smokers (81%) and 76.3% of them visiting their gynaecologists once a year. In addition, a high percentage of female healthcare workers have had the Pap test (88%). This number is similar to the 87.6% of women in the general population in Greece that reported to have had a Pap test . HoweverResults in different countries vary. For example, in a tertiary care hospital in Pakistan, only 61% of the nursing staff knew that HPV infection might lead to cervical cancer . However97% of our study participants were aware that cervical cancer is preventable. 10.5% reported avoiding smoking, 51% reported conservative sexual relations, 44% reported frequent check-up by gynaecologist and 80.5% reported the Pap test as important for cervical cancer prevention. This is different from a similar study we conducted among Greek female healthcare workers where 81.3% reported the Pap test but only 6.6% reported conservative sexual relations and 10% reported frequent check-up by gynaecologist . Thus, wOnly 81.67% of the female healthcare workers in our study knew about the HPV vaccine. However, awareness in Cyprus was better compared to other countries such as India where only 18% of nurses in a rural area knew about the HPV vaccine . The accThis study has some limitations as well. We sampled only from hospitals in two of the five districts in Cyprus. Knowledge and screening behaviour may be different in the other districts. Due to privacy and confidentiality laws, there was no random selection of healthcare professionals from each hospital/clinic but rather everyone was invited to answer the questionnaire by the hospital administration. It may be that those who answered the questionnaire are more attentive to their health than those who did not. Another limitation is that we included in our analysis questionnaires with some missing questions because we felt by excluding them we may be creating other biases.Our study established that there is a high percentage of female healthcare workers who undergo cervical cancer screening in Cyprus. However, there were some misconceptions about HPV transmission and preventive measures for cervical cancer. This might be due to the fact that this group has access to gynaecologists and hence are advised to do the Pap test; however, they do not necessarily know details about cervical cancer prevention. These misconceptions should be addressed since healthcare workers are health promotion ambassadors. Finally, the reluctance surrounding HPV vaccination should be addressed by providing further vaccine-related education to healthcare professionals so that they will feel more inclined to promote it to their patients and thus increase HPV vaccination rates in their communities.This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.The authors declare that they have no conflicts of interest.