192 research outputs found

    A Potential Role for the Interaction of Wolbachia Surface Proteins with the Brugia malayi Glycolytic Enzymes and Cytoskeleton in Maintenance of Endosymbiosis

    Get PDF
    The human filarial parasite Brugia malayi harbors an endosymbiotic bacterium of the genus Wolbachia. The Wolbachia represent an attractive target for the control of filarial induced disease as elimination of the bacteria affects molting, reproduction and survival of the worms. The molecular basis for the symbiotic relationship between Wolbachia and their filarial hosts has yet to be elucidated. To identify proteins involved in this process, we focused on the Wolbachia surface proteins (WSPs), which are known to be involved in bacteria-host interactions in other bacterial systems. Two WSP-like proteins (wBm0152 and wBm0432) were localized to various host tissues of the B. malayi female adult worms and are present in the excretory/secretory products of the worms. We provide evidence that both of these proteins bind specifically to B. malayi crude protein extracts and to individual filarial proteins to create functional complexes. The wBm0432 interacts with several key enzymes involved in the host glycolytic pathway, including aldolase and enolase. The wBm0152 interacts with the host cytoskeletal proteins actin and tubulin. We also show these interactions in vitro and have verified that wBm0432 and B. malayi aldolase, as well as wBm0152 and B. malayi actin, co-localize to the vacuole surrounding Wolbachia. We propose that both WSP protein complexes interact with each other via the aldolase-actin link and/or via the possible interaction between the host's enolase and the cytoskeleton, and play a role in Wolbachia distribution during worm growth and embryogenesis. © 2013 Melnikow et al

    Potential involvement of Brugia malayi cysteine proteases in the maintenance of the endosymbiotic relationship with Wolbachia

    Get PDF
    Brugia malayi, a parasitic nematode that causes lymphatic filariasis, harbors endosymbiotic intracellular bacteria, Wolbachia, that are required for the development and reproduction of the worm. The essential nature of this endosymbiosis led to the development of anti- Wolbachia chemotherapeutic approaches for the treatment of human filarial infections. Our study is aimed at identifying specific proteins that play a critical role in this endosymbiotic relationship leading to the identification of potential targets in the adult worms. Filarial cysteine proteases are known to be involved in molting and embryogenesis, processes shown to also be Wolbachia dependent. Based on the observation that cysteine protease transcripts are differentially regulated in response to tetracycline treatment, we focused on defining their role in symbiosis. We observe a bimodal regulation pattern of transcripts encoding cysteine proteases when in vitro tetracycline treated worms were examined. Using tetracycline-treated infertile female worms and purified embryos we established that the first peak of the bimodal pattern corresponds to embryonic transcripts while the second takes place within the hypodermis of the adult worms. Localization studies of the native proteins corresponding to Bm-cpl-3 and Bm-cpl-6 indicate that they are present in the area surrounding Wolbachia, and, in some cases, the proteins appear localized within the bacteria. Both proteins were also found in the inner bodies of microfilariae. The possible role of these cysteine proteases during development and endosymbiosis was further characterized using RNAi. Reduction in Bm-cpl-3 and Bm-cpl-6 transcript levels was accompanied by hindered microfilarial development and release, and reduced Wolbachia DNA levels, making these enzymes strong drug target candidates

    Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care: Analysis Using Process Mining

    Full text link
    [EN] Background: Public health in several countries is characterized by a shortage of professionals and a lack of economic resources. Monitoring and redesigning processes can foster the success of health care institutions, enabling them to provide a quality service while simultaneously reducing costs. Process mining, a discipline that extracts knowledge from information system data to analyze operational processes, affords an opportunity to understand health care processes. Objective: Health care processes are highly flexible and multidisciplinary, and health care professionals are able to coordinate in a variety of different ways to treat a diagnosis. The aim of this work was to understand whether the ways in which professionals coordinate their work affect the clinical outcome of patients. Methods: This paper proposes a method based on the use of process mining to identify patterns of collaboration between physician, nurse, and dietitian in the treatment of patients with type 2 diabetes mellitus and to compare these patterns with the clinical evolution of the patients within the context of primary care. Clustering is used as part of the preprocessing of data to manage the variability, and then process mining is used to identify patterns that may arise. Results: The method is applied in three primary health care centers in Santiago, Chile. A total of seven collaboration patterns were identified, which differed primarily in terms of the number of disciplines present, the participation intensity of each discipline, and the referrals between disciplines. The pattern in which the three disciplines participated in the most equitable and comprehensive manner had a lower proportion of highly decompensated patients compared with those patterns in which the three disciplines participated in an unbalanced manner. Conclusions: By discovering which collaboration patterns lead to improved outcomes, health care centers can promote the most successful patterns among their professionals so as to improve the treatment of patients. Process mining techniques are useful for discovering those collaborations patterns in flexible and unstructured health care processes.This paper was partially funded by the National Commission for Scientific and Technological Research, the Formation of Advanced Human Capital Program and the National Fund for Scientific and Technological Development (CONICYT-PCHA/Doctorado Nacional/2016-21161705 and CONICYT-FONDECYT/1150365; Chile). The authors would like to thank Ancora UC primary health care centers for their help with this research. The founding sponsors had no role in the design of the study in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.Conca, T.; Saint Pierre, C.; Herskovic, V.; Sepulveda, M.; Capurro, D.; Prieto, F.; Fernández Llatas, C. (2018). Multidisciplinary Collaboration in the Treatment of Patients With Type 2 Diabetes in Primary Care: Analysis Using Process Mining. JOURNAL OF MEDICAL INTERNET RESEARCH. 20(4). https://doi.org/10.2196/jmir.8884S204Chen, C.-C., Tseng, C.-H., & Cheng, S.-H. (2013). Continuity of Care, Medication Adherence, and Health Care Outcomes Among Patients With Newly Diagnosed Type 2 Diabetes. Medical Care, 51(3), 231-237. doi:10.1097/mlr.0b013e31827da5b9International Diabetes FederationIDF20152018-03-19IDF Diabetes Atlas 7th Edition (2015) https://www.idf.org/e-library/epidemiology-research/diabetes-atlas/13-diabetes-atlas-seventh-edition.htmlMinisterio de Salud de Chileminsal.cl20102018-03-23Encuesta Nacional de Salud ENS Chile 2009-2010 http://www.minsal.cl/estudios_encuestas_salud/Ministerio de Salud de Chileminsal.cl20102018-03-20Guía Clinica Diabetes Mellitus Tipo 2 http://www.minsal.cl/portal/url/item/72213ed52c3e23d1e04001011f011398.pdfSapunar Z., J. (2016). EPIDEMIOLOGÍA DE LA DIABETES MELLITUS EN CHILE. Revista Médica Clínica Las Condes, 27(2), 146-151. doi:10.1016/j.rmclc.2016.04.003World Health Organizationwho.int2018-03-20Global Report on Diabetes http://www.who.int/diabetes/global-report/en/Poblete, F., Glasinovic, A., Sapag, J., Barticevic, N., Arenas, A., & Padilla, O. (2015). Apoyo social y salud cardiovascular: adaptación de una escala de apoyo social en pacientes hipertensos y diabéticos en la atención primaria chilena. Atención Primaria, 47(8), 523-531. doi:10.1016/j.aprim.2014.10.010Tuligenga, R. H., Dugravot, A., Tabák, A. G., Elbaz, A., Brunner, E. J., Kivimäki, M., & Singh-Manoux, A. (2014). Midlife type 2 diabetes and poor glycaemic control as risk factors for cognitive decline in early old age: a post-hoc analysis of the Whitehall II cohort study. The Lancet Diabetes & Endocrinology, 2(3), 228-235. doi:10.1016/s2213-8587(13)70192-xGamiochipi, M., Cruz, M., Kumate, J., & Wacher, N. H. (2016). Effect of an intensive metabolic control lifestyle intervention in type-2 diabetes patients. Patient Education and Counseling, 99(7), 1184-1189. doi:10.1016/j.pec.2016.01.017Wagner, E. H. (2001). Effect of Improved Glycemic Control on Health Care Costs and Utilization. JAMA, 285(2), 182. doi:10.1001/jama.285.2.182McDonald, J., Jayasuriya, R., & Harris, M. F. (2012). The influence of power dynamics and trust on multidisciplinary collaboration: a qualitative case study of type 2 diabetes mellitus. BMC Health Services Research, 12(1). doi:10.1186/1472-6963-12-63Gucciardi, E., Espin, S., Morganti, A., & Dorado, L. (2016). Exploring interprofessional collaboration during the integration of diabetes teams into primary care. BMC Family Practice, 17(1). doi:10.1186/s12875-016-0407-1Caron, F., Vanthienen, J., Vanhaecht, K., Limbergen, E. V., De Weerdt, J., & Baesens, B. (2014). Monitoring care processes in the gynecologic oncology department. Computers in Biology and Medicine, 44, 88-96. doi:10.1016/j.compbiomed.2013.10.015Rothman, A. A., & Wagner, E. H. (2003). Chronic Illness Management: What Is the Role of Primary Care? Annals of Internal Medicine, 138(3), 256. doi:10.7326/0003-4819-138-3-200302040-00034Organisation for Economic Co-operation and DevelopmentOECD20162018-03-20OECD Health Policy Overview: Health Policy in Chile http://www.oecd.org/els/health-systems/health-policy-in-your-country.htmRojas, E., Munoz-Gama, J., Sepúlveda, M., & Capurro, D. (2016). Process mining in healthcare: A literature review. Journal of Biomedical Informatics, 61, 224-236. doi:10.1016/j.jbi.2016.04.007Fernandez-Llatas, C., Lizondo, A., Monton, E., Benedi, J.-M., & Traver, V. (2015). Process Mining Methodology for Health Process Tracking Using Real-Time Indoor Location Systems. Sensors, 15(12), 29821-29840. doi:10.3390/s151229769Mans, R. S., van der Aalst, W. M. P., & Vanwersch, R. J. B. (2015). Process Mining in Healthcare. SpringerBriefs in Business Process Management. doi:10.1007/978-3-319-16071-9Van der Aalst, W. M. P. (2011). Process Mining. doi:10.1007/978-3-642-19345-3Kim, E., Kim, S., Song, M., Kim, S., Yoo, D., Hwang, H., & Yoo, S. (2013). Discovery of Outpatient Care Process of a Tertiary University Hospital Using Process Mining. Healthcare Informatics Research, 19(1), 42. doi:10.4258/hir.2013.19.1.42Harper, P. R., Sayyad, M. G., de Senna, V., Shahani, A. K., Yajnik, C. S., & Shelgikar, K. M. (2003). A systems modelling approach for the prevention and treatment of diabetic retinopathy. European Journal of Operational Research, 150(1), 81-91. doi:10.1016/s0377-2217(02)00787-7Rebuge, Á., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99-116. doi:10.1016/j.is.2011.01.003Ferreira, D., Zacarias, M., Malheiros, M., & Ferreira, P. (2007). Approaching Process Mining with Sequence Clustering: Experiments and Findings. Business Process Management, 360-374. doi:10.1007/978-3-540-75183-0_26Cheong, L. H., Armour, C. L., & Bosnic-Anticevich, S. Z. (2013). Multidisciplinary collaboration in primary care: through the eyes of patients. Australian Journal of Primary Health, 19(3), 190. doi:10.1071/py12019Boyle, E., Saunders, R., & Drury, V. (2016). A qualitative study of patient experiences of Type 2 Diabetes care delivered comparatively by General Practice Nurses and Medical Practitioners. Journal of Clinical Nursing, 25(13-14), 1977-1986. doi:10.1111/jocn.13219UddinSHossainLEffects of Physician Collaboration Network on Hospital Outcomes2012Fifth Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2012)2012Melbourne, AustraliaBorgermans, L., Goderis, G., Van Den Broeke, C., Verbeke, G., Carbonez, A., Ivanova, A., … Grol, R. (2009). Interdisciplinary diabetes care teams operating on the interface between primary and specialty care are associated with improved outcomes of care: findings from the Leuven Diabetes Project. BMC Health Services Research, 9(1). doi:10.1186/1472-6963-9-179Bosch, M., Dijkstra, R., Wensing, M., van der Weijden, T., & Grol, R. (2008). Organizational culture, team climate and diabetes care in small office-based practices. BMC Health Services Research, 8(1). doi:10.1186/1472-6963-8-180Counsell, S. R., Callahan, C. M., Clark, D. O., Tu, W., Buttar, A. B., Stump, T. E., & Ricketts, G. D. (2007). Geriatric Care Management for Low-Income Seniors. JAMA, 298(22), 2623. doi:10.1001/jama.298.22.2623Anderson, J. G. (2002). Evaluation in health informatics: social network analysis. Computers in Biology and Medicine, 32(3), 179-193. doi:10.1016/s0010-4825(02)00014-8Gray, J. E., Davis, D. A., Pursley, D. M., Smallcomb, J. E., Geva, A., & Chawla, N. V. (2010). Network Analysis of Team Structure in the Neonatal Intensive Care Unit. PEDIATRICS, 125(6), e1460-e1467. doi:10.1542/peds.2009-2621Mian, O., Koren, I., & Rukholm, E. (2012). Nurse practitioners in Ontario primary healthcare: Referral patterns and collaboration with other healthcare professionals. Journal of Interprofessional Care, 26(3), 232-239. doi:10.3109/13561820.2011.650300Crossley, N., Bellotti, E., Edwards, G., Everett, M. G., Koskinen, J., & Tranmer, M. (2015). Social Network Analysis for Ego-Nets. doi:10.4135/9781473911871Ministerio de Salud de Chile2018-03-20Fondo Nacional de Salud https://www.fonasa.cl/sites/fonasa/beneficiariosGoldstein, D. E., Little, R. R., Lorenz, R. A., Malone, J. I., Nathan, D., Peterson, C. M., & Sacks, D. B. (2004). Tests of Glycemia in Diabetes. Diabetes Care, 27(7), 1761-1773. doi:10.2337/diacare.27.7.1761Meduru, P., Helmer, D., Rajan, M., Tseng, C.-L., Pogach, L., & Sambamoorthi, U. (2007). Chronic Illness with Complexity: Implications for Performance Measurement of Optimal Glycemic Control. Journal of General Internal Medicine, 22(S3), 408-418. doi:10.1007/s11606-007-0310-5Vermeire, E., Hearnshaw, H., Van Royen, P., & Denekens, J. (2001). Patient adherence to treatment: three decades of research. A comprehensive review. Journal of Clinical Pharmacy and Therapeutics, 26(5), 331-342. doi:10.1046/j.1365-2710.2001.00363.xKarter, A. J., Parker, M. M., Moffet, H. H., Ahmed, A. T., Ferrara, A., Liu, J. Y., & Selby, J. V. (2004). Missed Appointments and Poor Glycemic Control. Medical Care, 42(2), 110-115. doi:10.1097/01.mlr.0000109023.64650.73World Health Organization20032018-03-20Adherence to long-term therapies: evidence for action http://www.who.int/chp/knowledge/publications/adherence_report/en/Toth, E. L., Majumdar, S. R., Guirguis, L. M., Lewanczuk, R. Z., Lee, T. K., & Johnson, J. A. (2003). Compliance with Clinical Practice Guidelines for Type 2 Diabetes in Rural Patients: Treatment Gaps and Opportunities for Improvement. Pharmacotherapy, 23(5), 659-665. doi:10.1592/phco.23.5.659.32203Melnikow, J., & Kiefe, C. (1994). Patient compliance and medical research. Journal of General Internal Medicine, 9(2), 96-105. doi:10.1007/bf02600211Fernandez-Llatas, C., Valdivieso, B., Traver, V., & Benedi, J. M. (2014). Using Process Mining for Automatic Support of Clinical Pathways Design. Data Mining in Clinical Medicine, 79-88. doi:10.1007/978-1-4939-1985-7_5Fernández-Llatas, C., Benedi, J.-M., García-Gómez, J., & Traver, V. (2013). Process Mining for Individualized Behavior Modeling Using Wireless Tracking in Nursing Homes. Sensors, 13(11), 15434-15451. doi:10.3390/s131115434Wishah, R. A., Al-Khawaldeh, O. A., & Albsoul, A. M. (2015). Impact of pharmaceutical care interventions on glycemic control and other health-related clinical outcomes in patients with type 2 diabetes: Randomized controlled trial. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 9(4), 271-276. doi:10.1016/j.dsx.2014.09.00

    Use of tamoxifen and raloxifene for breast cancer chemoprevention in 2010

    Get PDF
    PURPOSE: Two selective estrogen receptor modulators (SERMs), tamoxifen and raloxifene, have been shown in randomized clinical trials to reduce the risk of developing primary invasive breast cancer (IBC) in high-risk women. In 1998, the U.S. Food and Drug Administration (FDA) used these studies as a basis for approving tamoxifen for primary breast chemoprevention in both premenopausal and postmenopausal women at high risk. In 2007, the FDA approved raloxifene for primary breast cancer chemoprevention for postmenopausal women. METHODS: Data from the year 2010 National Health Interview Survey (NHIS) were analyzed to estimate the prevalence of tamoxifen and raloxifene use for chemoprevention of primary breast cancers among U.S. women. RESULTS: Prevalence of use of chemopreventive agents for primary tumors was 20,598 (95% CI, 518–114,864) for U.S. women aged 35 to 79 for tamoxifen. Prevalence was 96,890 (95% CI, 41,277–192,391) for U.S. women aged 50 to79 for raloxifene. CONCLUSION: Use of tamoxifen and raloxifene for prevention of primary breast cancers continues to be low. In 2010, women reporting medication use for breast cancer chemoprevention were primarily using the more recently FDA-approved drug raloxifene. Multiple possible explanations for the low use exist, including lack of awareness and/or concern about side effects among primary care physicians and patients

    Effect of incentives on insecticide-treated bed net use in sub-Saharan Africa: a cluster randomized trial in Madagascar

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Insecticide-treated bed nets (ITNs) have been shown to reduce morbidity and mortality due to malaria in sub-Saharan Africa. Strategies using incentives to increase ITN use could be more efficient than traditional distribution campaigns. To date, behavioural incentives have been studied mostly in developed countries. No study has yet looked at the effect of incentives on the use of ITNs. Reported here are the results of a cluster randomized controlled trial testing household-level incentives for ITN use following a free ITN distribution campaign in Madagascar.</p> <p>Methods</p> <p>The study took place from July 2007 until February 2008. Twenty-one villages were randomized to either intervention or control clusters. Households in both clusters received a coupon redeemable for one ITN. After one month, intervention households received a bonus for ITN use, determined by visual confirmation of a mounted ITN. Data were collected at baseline, one month and six months. Both unadjusted and adjusted results, using cluster specific methods, are presented.</p> <p>Results</p> <p>At baseline, 8.5% of households owned an ITN and 6% were observed to have a net mounted over a bed in the household. At one month, there were no differences in ownership between the intervention and control groups (99.5% vs. 99.4%), but net use was substantially higher in the intervention group (99% vs. 78%), with an adjusted risk ratio of 1.24 (95% CI: 1.10 to 1.40; p < 0.001). After six months, net ownership had decreased in the intervention compared to the control group (96.7% vs. 99.7%), with an adjusted risk ratio of 0.97 (p < 0.01). There was no difference between the groups in terms of ITN use at six months; however, intervention households were more likely to use a net that they owned (96% vs. 90%; p < 0.001).</p> <p>Conclusions</p> <p>Household-level incentives have the potential to significantly increase the use of ITNs in target households in the immediate-term, but, over time, the use of ITNs is similar to households that did not receive incentives. Providing incentives for behaviour change is a promising tool that can complement traditional ITN distribution programmes and improve the effectiveness of ITN programmes in protecting vulnerable populations, especially in the short-term.</p

    Explaining Ethnic Differences in Late Antenatal Care Entry by Predisposing, Enabling and Need Factors in the Netherlands. The Generation R Study

    Get PDF
    Despite compulsory health insurance in Europe, ethnic differences in access to health care exist. The objective of this study is to investigate how ethnic differences between Dutch and non-Dutch women with respect to late entry into antenatal care provided by community midwifes can be explained by need, predisposing and enabling factors. Data were obtained from the Generation R Study. The Generation R Study is a multi-ethnic population-based prospective cohort study conducted in the city of Rotterdam. In total, 2,093 pregnant women with a Dutch, Moroccan, Turkish, Cape Verdean, Antillean, Surinamese Creole and Surinamese Hindustani background were included in this study. We examined whether ethnic differences in late antenatal care entry could be explained by need, predisposing and enabling factors. Subsequently, logistic regression analysis was used to assess the independent role of explanatory variables in the timing of antenatal care entry. The main outcome measure was late entry into antenatal care (gestational age at first visit after 14 weeks). With the exception of Surinamese-Hindustani women, the percentage of mothers entering antenatal care late was higher in all non-Dutch compared to Dutch mothers. We could explain differences between Turkish (OR = 0.95, CI: 0.57–1.58), Cape Verdean (OR = 1.65. CI: 0.96–2.82) and Dutch women. Other differences diminished but remained significant (Moroccan: OR = 1,74, CI: 1.07–2.85; Dutch Antillean OR 1.80, CI: 1.04–3.13). We found that non-Dutch mothers were more likely to enter antenatal care later than Dutch mothers. Because we are unable to explain fully the differences regarding Moroccan, Surinamese-Creole and Antillean women, future research should focus on differences between 1st and 2nd generation migrants, as well as on language barriers that may hinder access to adequate information about the Dutch obstetric system

    Common Changes in Global Gene Expression Induced by RNA Polymerase Inhibitors in shigella flexneri

    Get PDF
    Characterization of expression profile of organisms in response to antimicrobials provides important information on the potential mechanism of action of the drugs. The special expression signature can be used to predict whether other drugs act on the same target. Here, the common response of Shigella flexneri to two inhibitors of RNA polymerase was examined using gene expression profiling. Consistent with similar effects of the two drugs, the gene expression profiles indicated that responses of the bacteria to these drugs were roughly the same, with 225 genes affected commonly. Of them, 88 were induced and 137 were repressed. Real-time PCR was performed for selected genes to verify the microarray results. Analysis of the expression data revealed that more than 30% of the plasmid-encoded genes on the array were up-regulated by the antibiotics including virF regulon, other virulence-related genes, and genes responsible for plasmid replication, maintenance, and transfer. In addition, some chromosome-encoded genes involved in virulence and genes acquired from horizontal transfer were also significantly up-regulated. However, the expression of genes encoding the beta-subunit of RNA polymerase was increased moderately. The repressed genes include those that code for products associated with the ribosome, citrate cycle, glycolysis, thiamine biosynthesis, purine metabolism, fructose metabolism, mannose metabolism, and cold shock proteins. This study demonstrates that the two antibiotics induce rapid cessation of RNA synthesis resulting in inhibition of translation components. It also indicates that the production of virulence factors involved in intercellular dissemination, tissue invasion and inflammatory destruction may be enhanced through derepressing horizontal transfer genes by the drugs

    Complex Calculations: How Drug Use During Pregnancy Becomes a Barrier to Prenatal Care

    Get PDF
    Pregnant women who use drugs are more likely to receive little or no prenatal care. This study sought to understand how drug use and factors associated with drug use influence women’s prenatal care use. A total of 20 semi-structured interviews and 2 focus groups were conducted with a racially/ethnically diverse sample of low-income women using alcohol and drugs in a California county. Women using drugs attend and avoid prenatal care for reasons not connected to their drug use: concern for the health of their baby, social support, and extrinsic barriers such as health insurance and transportation. Drug use itself is a barrier for a few women. In addition to drug use, women experience multiple simultaneous risk factors. Both the drug use and the multiple simultaneous risk factors make resolving extrinsic barriers more difficult. Women also fear the effects of drug use on their baby’s health and fear being reported to Child Protective Services, each of which influence women’s prenatal care use. Increasing the number of pregnant women who use drugs who receive prenatal care requires systems-level rather than only individual-level changes. These changes require a paradigm shift to viewing drug use in context of the person and society and acceptance of responsibility for unintended consequences of public health bureaucratic procedures and messages about effects of drug use during pregnancy

    Analysis of genetic copy number changes in cervical disease progression

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Cervical dysplasia and tumorigenesis have been linked with numerous chromosomal aberrations. The goal of this study was to evaluate 35 genomic regions associated with cervical disease and to select those which were found to have the highest frequency of aberration for use as probes in fluorescent in-situ hybridization.</p> <p>Methods</p> <p>The frequency of gains and losses using fluorescence in-situ hybridization were assessed in these 35 regions on 30 paraffin-embedded cervical biopsy specimens. Based on this assessment, 6 candidate fluorescently labeled probes (8q24, Xp22, 20q13, 3p14, 3q26, CEP15) were selected for additional testing on a set of 106 cervical biopsy specimens diagnosed as Normal, CIN1, CIN2, CIN3, and SCC. The data were analyzed on the basis of signal mean, % change of signal mean between histological categories, and % positivity.</p> <p>Results</p> <p>The study revealed that the chromosomal regions with the highest frequency of copy number gains and highest combined sensitivity and specificity in high-grade cervical disease were 8q24 and 3q26. The cytological application of these two probes was then evaluated on 118 ThinPrep™ samples diagnosed as Normal, ASCUS, LSIL, HSIL and Cancer to determine utility as a tool for less invasive screening. Using gains of either 8q24 or 3q26 as a positivity criterion yielded specificity (Normal +LSIL+ASCUS) of 81.0% and sensitivity (HSIL+Cancer) of 92.3% based on a threshold of 4 positive cells.</p> <p>Conclusions</p> <p>The application of a FISH assay comprised of chromosomal probes 8q24 and 3q26 to cervical cytology specimens confirms the positive correlation between increasing dysplasia and copy gains and shows promise as a marker in cervical disease progression.</p
    corecore