151 research outputs found

    Prevalence of antibodies to a new histo-blood system: the FORS system

    Get PDF
    In 1987, three unrelated English families were reported with a putative blood subgroup called Apae. Swedish researchers later found evidence leading to abolishment of the Apae subgroup and establishment instead of the FORS blood group system (System 31 - ISBT, 2012). It is important to know the prevalence of antibodies in order to make the best decisions in transfusion medicine. Cells expressing the Forssman saccharide, such as sheep erythrocytes, are needed to detect the anti-Forssman antibody. The aim of this study was to define the prevalence of human anti-Forssman antibody.info:eu-repo/semantics/publishedVersio

    Breast-Milk Substitutes: A New Old-Threat for Breastfeeding Policy in Developing Countries. A Case Study in a Traditionally High Breastfeeding Country

    Get PDF
    Background: Developing countries with traditionally breastfeeding are now experiencing the increasing pressure of formula milk marketing. This may endanger lives and undermine the efforts of national policies in achieving the objectives of the Millennium Development Goals. We examined the use of, and factors for use, of all available breast-milk substitutes (BMS) in a country with a traditionally high rate of breastfeeding. Methods: Randomised multi-stage sampling surveys in 90 villages in 12/17 provinces in Laos. Participants: 1057 mothers with infants under 24 months of age. Tools: 50-query questionnaire and a poster of 22 BMS (8 canned or powdered milk; 6 non-dairy; 6 formulas; 2 non-formulas). Outcome measures included: prevalence of use and age of starting BMS in relation to socio-demographic characteristics and information sources, by univariate and multivariate analyses

    The Fuzzy Project Scheduling Problem with Minimal Generalized Precedence Relations

    Full text link
    In scheduling, estimations are affected by the imprecision of limited information on future events, and the reduction in the number and level of detail of activities. Overlapping of processes and activities requires the study of their continuity, along with analysis of the risks associated with imprecision. In this line, this paper proposes a fuzzy heuristic model for the Project Scheduling Problem with flows and minimal feeding, time and work Generalized Precedence Relations with a realistic approach to overlapping, in which the continuity of processes and activities is allowed in a discretionary way. This fuzzy algorithm handles the balance of process flows, and computes the optimal fragmentation of tasks, avoiding the interruption of the critical path and reverse criticality. The goodness of this approach is tested on several problems found in the literature; furthermore, an example of a 15-story building was used to compare the better performance of the algorithm implemented in Visual Basic for Applications (Excel) over that same example input in Primavera© P6 Professional V8.2.0, using five different scenarios.This research was supported by the FAPA program of Universidad de Los Andes, Colombia. The authors would like to thank the research group of Construction Engineering and Management (INgeco) of Universidad de Los Andes, and the five anonymous referees for their helpful and constructive suggestions.Ponz Tienda, JL.; Pellicer Armiñana, E.; Benlloch Marco, J.; Andrés Romano, C. (2015). The Fuzzy Project Scheduling Problem with Minimal Generalized Precedence Relations. Computer-Aided Civil and Infrastructure Engineering. 30(11):872-891. doi:10.1111/mice.12166S8728913011Adeli, H., & Park, H. S. (1995). Optimization of space structures by neural dynamics. Neural Networks, 8(5), 769-781. doi:10.1016/0893-6080(95)00026-vAdeli, H., & Karim, A. (1997). Scheduling/Cost Optimization and Neural Dynamics Model for Construction. Journal of Construction Engineering and Management, 123(4), 450-458. doi:10.1061/(asce)0733-9364(1997)123:4(450)Adeli, H., & Wu, M. (1998). Regularization Neural Network for Construction Cost Estimation. Journal of Construction Engineering and Management, 124(1), 18-24. doi:10.1061/(asce)0733-9364(1998)124:1(18)Alarcón, L. F., Ashley, D. B., de Hanily, A. S., Molenaar, K. R., & Ungo, R. (2011). Risk Planning and Management for the Panama Canal Expansion Program. Journal of Construction Engineering and Management, 137(10), 762-771. doi:10.1061/(asce)co.1943-7862.0000317Ammar, M. A. (2013). LOB and CPM Integrated Method for Scheduling Repetitive Projects. Journal of Construction Engineering and Management, 139(1), 44-50. doi:10.1061/(asce)co.1943-7862.0000569Arditi, D., & Bentotage, S. N. (1996). System for Scheduling Highway Construction Projects. Computer-Aided Civil and Infrastructure Engineering, 11(2), 123-139. doi:10.1111/j.1467-8667.1996.tb00316.xBai, L., Yan, L., & Ma, Z. M. (2014). Querying fuzzy spatiotemporal data using XQuery. Integrated Computer-Aided Engineering, 21(2), 147-162. doi:10.3233/ica-130454Ballesteros-Pérez, P., González-Cruz, M. C., Cañavate-Grimal, A., & Pellicer, E. (2013). Detecting abnormal and collusive bids in capped tendering. Automation in Construction, 31, 215-229. doi:10.1016/j.autcon.2012.11.036Bartusch, M., Möhring, R. H., & Radermacher, F. J. (1988). Scheduling project networks with resource constraints and time windows. Annals of Operations Research, 16(1), 199-240. doi:10.1007/bf02283745Bianco, L., & Caramia, M. (2011). Minimizing the completion time of a project under resource constraints and feeding precedence relations: a Lagrangian relaxation based lower bound. 4OR, 9(4), 371-389. doi:10.1007/s10288-011-0168-6Bonnal, P., Gourc, D., & Lacoste, G. (2004). Where Do We Stand with Fuzzy Project Scheduling? Journal of Construction Engineering and Management, 130(1), 114-123. doi:10.1061/(asce)0733-9364(2004)130:1(114)Brunelli, M., & Mezei, J. (2013). How different are ranking methods for fuzzy numbers? A numerical study. International Journal of Approximate Reasoning, 54(5), 627-639. doi:10.1016/j.ijar.2013.01.009Buckley, J. J., & Eslami, E. (2002). An Introduction to Fuzzy Logic and Fuzzy Sets. doi:10.1007/978-3-7908-1799-7Castro-Lacouture, D., Süer, G. A., Gonzalez-Joaqui, J., & Yates, J. K. (2009). Construction Project Scheduling with Time, Cost, and Material Restrictions Using Fuzzy Mathematical Models and Critical Path Method. Journal of Construction Engineering and Management, 135(10), 1096-1104. doi:10.1061/(asce)0733-9364(2009)135:10(1096)Chanas, S., & Kamburowski, J. (1981). The use of fuzzy variables in pert. Fuzzy Sets and Systems, 5(1), 11-19. doi:10.1016/0165-0114(81)90030-0In Seong Chang, Yasuhiro Tsujimura, Mitsuo Gen, & Tatsumi Tozawa. (1995). An efficient approach for large scale project planning based on fuzzy Delphi method. Fuzzy Sets and Systems, 76(3), 277-288. doi:10.1016/0165-0114(94)00385-4Chen, C.-T., & Huang, S.-F. (2007). Applying fuzzy method for measuring criticality in project network. Information Sciences, 177(12), 2448-2458. doi:10.1016/j.ins.2007.01.035Shyi-Ming Chen, & Tao-Hsing Chang. (2001). Finding multiple possible critical paths using fuzzy PERT. IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics), 31(6), 930-937. doi:10.1109/3477.969496Damci, A., Arditi, D., & Polat, G. (2013). Resource Leveling in Line-of-Balance Scheduling. Computer-Aided Civil and Infrastructure Engineering, 28(9), 679-692. doi:10.1111/mice.12038Dell’Orco, M., & Mellano, M. (2013). A New User-Oriented Index, Based on a Fuzzy Inference System, for Quality Evaluation of Rural Roads. Computer-Aided Civil and Infrastructure Engineering, 28(8), 635-647. doi:10.1111/mice.12021Deng, H. (2014). Comparing and ranking fuzzy numbers using ideal solutions. Applied Mathematical Modelling, 38(5-6), 1638-1646. doi:10.1016/j.apm.2013.09.012De Reyck, B., & Herroelen, willy. (1998). A branch-and-bound procedure for the resource-constrained project scheduling problem with generalized precedence relations. European Journal of Operational Research, 111(1), 152-174. doi:10.1016/s0377-2217(97)00305-6De Reyck, B., & Herroelen, W. (1999). The multi-mode resource-constrained project scheduling problem with generalized precedence relations. European Journal of Operational Research, 119(2), 538-556. doi:10.1016/s0377-2217(99)00151-4Dubois, D., Fargier, H., & Galvagnon, V. (2003). On latest starting times and floats in activity networks with ill-known durations. European Journal of Operational Research, 147(2), 266-280. doi:10.1016/s0377-2217(02)00560-xElmaghraby, S. E., & Kamburowski, J. (1992). The Analysis of Activity Networks Under Generalized Precedence Relations (GPRs). Management Science, 38(9), 1245-1263. doi:10.1287/mnsc.38.9.1245Fondahl , J. W. 1961 A Non-Computer Approach to the Critical Path Method for the Construction IndustryFougères, A.-J., & Ostrosi, E. (2013). Fuzzy agent-based approach for consensual design synthesis in product configuration. Integrated Computer-Aided Engineering, 20(3), 259-274. doi:10.3233/ica-130434Gil-Aluja, J. (2004). Fuzzy Sets in the Management of Uncertainty. Studies in Fuzziness and Soft Computing. doi:10.1007/978-3-540-39699-4Hajdu, M. (1997). Network Scheduling Techniques for Construction Project Management. Nonconvex Optimization and Its Applications. doi:10.1007/978-1-4757-5951-8Harris, R. B., & Ioannou, P. G. (1998). Scheduling Projects with Repeating Activities. Journal of Construction Engineering and Management, 124(4), 269-278. doi:10.1061/(asce)0733-9364(1998)124:4(269)Hejducki, Z. (2004). Sequencing problems in methods of organising construction processes. Engineering, Construction and Architectural Management, 11(1), 20-32. doi:10.1108/09699980410512638Hebert, J. E., & Deckro, R. F. (2011). Combining contemporary and traditional project management tools to resolve a project scheduling problem. Computers & Operations Research, 38(1), 21-32. doi:10.1016/j.cor.2009.12.004Herroelen, W., & Leus, R. (2005). Project scheduling under uncertainty: Survey and research potentials. European Journal of Operational Research, 165(2), 289-306. doi:10.1016/j.ejor.2004.04.002IBM 1968Jahani, E., Muhanna, R. L., Shayanfar, M. A., & Barkhordari, M. A. (2013). Reliability Assessment with Fuzzy Random Variables Using Interval Monte Carlo Simulation. Computer-Aided Civil and Infrastructure Engineering, 29(3), 208-220. doi:10.1111/mice.12028Karim, A., & Adeli, H. (1999). OO Information Model for Construction Project Management. Journal of Construction Engineering and Management, 125(5), 361-367. doi:10.1061/(asce)0733-9364(1999)125:5(361)Karim, A., & Adeli, H. (1999). CONSCOM: An OO Construction Scheduling and Change Management System. Journal of Construction Engineering and Management, 125(5), 368-376. doi:10.1061/(asce)0733-9364(1999)125:5(368)KARIM, A., & ADELI, H. (1999). A new generation software for construction scheduling and management. Engineering, Construction and Architectural Management, 6(4), 380-390. doi:10.1108/eb021126Kim, S.-G. (2012). CPM Schedule Summarizing Function of the Beeline Diagramming Method. Journal of Asian Architecture and Building Engineering, 11(2), 367-374. doi:10.3130/jaabe.11.367Kis, T. (2005). A branch-and-cut algorithm for scheduling of projects with variable-intensity activities. Mathematical Programming, 103(3), 515-539. doi:10.1007/s10107-004-0551-6Kolisch, R., & Sprecher, A. (1997). PSPLIB - A project scheduling problem library. European Journal of Operational Research, 96(1), 205-216. doi:10.1016/s0377-2217(96)00170-1Krishnan, V., Eppinger, S. D., & Whitney, D. E. (1997). A Model-Based Framework to Overlap Product Development Activities. Management Science, 43(4), 437-451. doi:10.1287/mnsc.43.4.437LEACHMAN, R. C., DTNCERLER, A., & KIM, S. (1990). Resource-Constrained Scheduling of Projects with Variable-Intensity Activities. IIE Transactions, 22(1), 31-40. doi:10.1080/07408179008964155Lim, T.-K., Yi, C.-Y., Lee, D.-E., & Arditi, D. (2014). Concurrent Construction Scheduling Simulation Algorithm. Computer-Aided Civil and Infrastructure Engineering, 29(6), 449-463. doi:10.1111/mice.12073Long, L. D., & Ohsato, A. (2008). Fuzzy critical chain method for project scheduling under resource constraints and uncertainty. International Journal of Project Management, 26(6), 688-698. doi:10.1016/j.ijproman.2007.09.012Lootsma, F. A. (1989). Stochastic and fuzzy Pert. European Journal of Operational Research, 43(2), 174-183. doi:10.1016/0377-2217(89)90211-7Malcolm, D. G., Roseboom, J. H., Clark, C. E., & Fazar, W. (1959). Application of a Technique for Research and Development Program Evaluation. Operations Research, 7(5), 646-669. doi:10.1287/opre.7.5.646Maravas, A., & Pantouvakis, J.-P. (2011). Fuzzy Repetitive Scheduling Method for Projects with Repeating Activities. Journal of Construction Engineering and Management, 137(7), 561-564. doi:10.1061/(asce)co.1943-7862.0000319PONZ TIENDA, J. L., BENLLOCH MARCO, J., ANDRÉS ROMANO, C., & SENABRE, D. (2011). Un algoritmo matricial RUPSP / GRUPSP «sin interrupción» para la planificación de la producción bajo metodología Lean Construction basado en procesos productivos. Revista de la construcción, 10(2), 90-103. doi:10.4067/s0718-915x2011000200009Ponz-Tienda, J. L., Pellicer, E., & Yepes, V. (2012). Complete fuzzy scheduling and fuzzy earned value management in construction projects. Journal of Zhejiang University SCIENCE A, 13(1), 56-68. doi:10.1631/jzus.a1100160Ponz-Tienda, J. L., Yepes, V., Pellicer, E., & Moreno-Flores, J. (2013). The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm. Automation in Construction, 29, 161-172. doi:10.1016/j.autcon.2012.10.003Prade, H. (1979). Using fuzzy set theory in a scheduling problem: A case study. Fuzzy Sets and Systems, 2(2), 153-165. doi:10.1016/0165-0114(79)90022-8Quintanilla, S., Pérez, Á., Lino, P., & Valls, V. (2012). Time and work generalised precedence relationships in project scheduling with pre-emption: An application to the management of Service Centres. European Journal of Operational Research, 219(1), 59-72. doi:10.1016/j.ejor.2011.12.018Rommelfanger, H. J. (1994). Network analysis and information flow in fuzzy environment. Fuzzy Sets and Systems, 67(1), 119-128. doi:10.1016/0165-0114(94)90212-7Senouci, A. B., & Adeli, H. (2001). Resource Scheduling Using Neural Dynamics Model of Adeli and Park. Journal of Construction Engineering and Management, 127(1), 28-34. doi:10.1061/(asce)0733-9364(2001)127:1(28)Seppänen, O., Evinger, J., & Mouflard, C. (2014). Effects of the location-based management system on production rates and productivity. Construction Management and Economics, 32(6), 608-624. doi:10.1080/01446193.2013.853881Shi, Q., & Blomquist, T. (2012). A new approach for project scheduling using fuzzy dependency structure matrix. International Journal of Project Management, 30(4), 503-510. doi:10.1016/j.ijproman.2011.11.003Srour, I. M., Abdul-Malak, M.-A. U., Yassine, A. A., & Ramadan, M. (2013). A methodology for scheduling overlapped design activities based on dependency information. Automation in Construction, 29, 1-11. doi:10.1016/j.autcon.2012.08.001Valls, V., & Lino, P. (2001). Annals of Operations Research, 102(1/4), 17-37. doi:10.1023/a:1010941729204Valls, V., Mart�, R., & Lino, P. (1996). A heuristic algorithm for project scheduling with splitting allowed. Journal of Heuristics, 2(1), 87-104. doi:10.1007/bf00226294Wang, Y.-M., Yang, J.-B., Xu, D.-L., & Chin, K.-S. (2006). On the centroids of fuzzy numbers. Fuzzy Sets and Systems, 157(7), 919-926. doi:10.1016/j.fss.2005.11.006Wiest, J. D. (1981). Precedence diagramming method: Some unusual characteristics and their implications for project managers. Journal of Operations Management, 1(3), 121-130. doi:10.1016/0272-6963(81)90015-2Yan, L., & Ma, Z. M. (2013). Conceptual design of object-oriented databases for fuzzy engineering information modeling. Integrated Computer-Aided Engineering, 20(2), 183-197. doi:10.3233/ica-130427Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338-353. doi:10.1016/s0019-9958(65)90241-xZeng, Z., Xu, J., Wu, S., & Shen, M. (2014). Antithetic Method-Based Particle Swarm Optimization for a Queuing Network Problem with Fuzzy Data in Concrete Transportation Systems. Computer-Aided Civil and Infrastructure Engineering, 29(10), 771-800. doi:10.1111/mice.12111Zhang, X., Li, Y., Zhang, S., & Schlick, C. M. (2013). Modelling and simulation of the task scheduling behavior in collaborative product development process. Integrated Computer-Aided Engineering, 20(1), 31-44. doi:10.3233/ica-12041

    SLUG/SNAI2 and Tumor Necrosis Factor Generate Breast Cells With CD44+/CD24- Phenotype

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Breast cancer cells with CD44+/CD24- cell surface marker expression profile are proposed as cancer stem cells (CSCs). Normal breast epithelial cells that are CD44+/CD24- express higher levels of stem/progenitor cell associated genes. We, amongst others, have shown that cancer cells that have undergone epithelial to mesenchymal transition (EMT) display the CD44+/CD24- phenotype. However, whether all genes that induce EMT confer the CD44+/CD24- phenotype is unknown. We hypothesized that only a subset of genes associated with EMT generates CD44+/CD24- cells.</p> <p>Methods</p> <p>MCF-10A breast epithelial cells, a subpopulation of which spontaneously acquire the CD44+/CD24- phenotype, were used to identify genes that are differentially expressed in CD44+/CD24- and CD44-/CD24+ cells. Ingenuity pathway analysis was performed to identify signaling networks that linked differentially expressed genes. Two EMT-associated genes elevated in CD44+/CD24- cells, SLUG and Gli-2, were overexpressed in the CD44-/CD24+ subpopulation of MCF-10A cells and MCF-7 cells, which are CD44-/CD24+. Flow cytometry and mammosphere assays were used to assess cell surface markers and stem cell-like properties, respectively.</p> <p>Results</p> <p>Two thousand thirty five genes were differentially expressed (p < 0.001, fold change ≥ 2) between the CD44+/CD24- and CD44-/CD24+ subpopulations of MCF-10A. Thirty-two EMT-associated genes including SLUG, Gli-2, ZEB-1, and ZEB-2 were expressed at higher levels in CD44+/CD24- cells. These EMT-associated genes participate in signaling networks comprising TGFβ, NF-κB, and human chorionic gonadotropin. Treatment with tumor necrosis factor (TNF), which induces NF-κB and represses E-cadherin, or overexpression of SLUG in CD44-/CD24+ MCF-10A cells, gave rise to a subpopulation of CD44+/CD24- cells. Overexpression of constitutively active p65 subunit of NF-κB in MCF-10A resulted in a dramatic shift to the CD44+/CD24+ phenotype. SLUG overexpression in MCF-7 cells generated CD44+/CD24+ cells with enhanced mammosphere forming ability. In contrast, Gli-2 failed to alter CD44 and CD24 expression.</p> <p>Conclusions</p> <p>EMT-mediated generation of CD44+/CD24- or CD44+/CD24+ cells depends on the genes that induce or are associated with EMT. Our studies reveal a role for TNF in altering the phenotype of breast CSC. Additionally, the CD44+/CD24+ phenotype, in the context of SLUG overexpression, can be associated with breast CSC "stemness" behavior based on mammosphere forming ability.</p

    Genomic and Proteomic Analysis of the Impact of Mitotic Quiescence on the Engraftment of Human CD34+ Cells

    Get PDF
    It is well established that in adults, long-term repopulating hematopoietic stem cells (HSC) are mitotically quiescent cells that reside in specialized bone marrow (BM) niches that maintain the dormancy of HSC. Our laboratory demonstrated that the engraftment potential of human HSC (CD34+ cells) from BM and mobilized peripheral blood (MPB) is restricted to cells in the G0 phase of cell cycle but that in the case of umbilical cord blood (UCB) -derived CD34+ cells, cell cycle status is not a determining factor in the ability of these cells to engraft and sustain hematopoiesis. We used this distinct in vivo behavior of CD34+ cells from these tissues to identify genes associated with the engraftment potential of human HSC. CD34+ cells from BM, MPB, and UCB were fractionated into G0 and G1 phases of cell cycle and subjected in parallel to microarray and proteomic analyses. A total of 484 target genes were identified to be associated with engraftment potential of HSC. System biology modeling indicated that the top four signaling pathways associated with these genes are Integrin signaling, p53 signaling, cytotoxic T lymphocyte-mediated apoptosis, and Myc mediated apoptosis signaling. Our data suggest that a continuum of functions of hematopoietic cells directly associated with cell cycle progression may play a major role in governing the engraftment potential of stem cells. While proteomic analysis identified a total of 646 proteins in analyzed samples, a very limited overlap between genomic and proteomic data was observed. These data provide a new insight into the genetic control of engraftment of human HSC from distinct tissues and suggest that mitotic quiescence may not be the requisite characteristic of engrafting stem cells, but instead may be the physiologic status conducive to the expression of genetic elements favoring engraftment

    Association between nutritional profiles of foods underlying Nutri-Score front-of-pack labels and mortality: EPIC cohort study in 10 European countries.

    Get PDF
    OBJECTIVE: To determine if the Food Standards Agency nutrient profiling system (FSAm-NPS), which grades the nutritional quality of food products and is used to derive the Nutri-Score front-of-packet label to guide consumers towards healthier food choices, is associated with mortality. DESIGN: Population based cohort study. SETTING: European Prospective Investigation into Cancer and Nutrition (EPIC) cohort from 23 centres in 10 European countries. PARTICIPANTS: 521 324 adults; at recruitment, country specific and validated dietary questionnaires were used to assess their usual dietary intakes. A FSAm-NPS score was calculated for each food item per 100 g content of energy, sugars, saturated fatty acids, sodium, fibre, and protein, and of fruit, vegetables, legumes, and nuts. The FSAm-NPS dietary index was calculated for each participant as an energy weighted mean of the FSAm-NPS score of all foods consumed. The higher the score the lower the overall nutritional quality of the diet. MAIN OUTCOME MEASURE: Associations between the FSAm-NPS dietary index score and mortality, assessed using multivariable adjusted Cox proportional hazards regression models. RESULTS: After exclusions, 501 594 adults (median follow-up 17.2 years, 8 162 730 person years) were included in the analyses. Those with a higher FSAm-NPS dietary index score (highest versus lowest fifth) showed an increased risk of all cause mortality (n=53 112 events from non-external causes; hazard ratio 1.07, 95% confidence interval 1.03 to 1.10, P<0.001 for trend) and mortality from cancer (1.08, 1.03 to 1.13, P<0.001 for trend) and diseases of the circulatory (1.04, 0.98 to 1.11, P=0.06 for trend), respiratory (1.39, 1.22 to 1.59, P<0.001), and digestive (1.22, 1.02 to 1.45, P=0.03 for trend) systems. The age standardised absolute rates for all cause mortality per 10 000 persons over 10 years were 760 (men=1237; women=563) for those in the highest fifth of the FSAm-NPS dietary index score and 661 (men=1008; women=518) for those in the lowest fifth. CONCLUSIONS: In this large multinational European cohort, consuming foods with a higher FSAm-NPS score (lower nutritional quality) was associated with a higher mortality for all causes and for cancer and diseases of the circulatory, respiratory, and digestive systems, supporting the relevance of FSAm-NPS to characterise healthier food choices in the context of public health policies (eg, the Nutri-Score) for European populations. This is important considering ongoing discussions about the potential implementation of a unique nutrition labelling system at the European Union level

    The state of HRM in the Middle East:Challenges and future research agenda

    Get PDF
    Based on a robust structured literature analysis, this paper highlights the key developments in the field of human resource management (HRM) in the Middle East. Utilizing the institutional perspective, the analysis contributes to the literature on HRM in the Middle East by focusing on four key themes. First, it highlights the topical need to analyze the context-specific nature of HRM in the region. Second, via the adoption of a systematic review, it highlights state of development in HRM in the research analysis set-up. Third, the analysis also helps to reveal the challenges facing the HRM function in the Middle East. Fourth, it presents an agenda for future research in the form of research directions. While doing the above, it revisits the notions of “universalistic” and “best practice” HRM (convergence) versus “best-fit” or context distinctive (divergence) and also alternate models/diffusion of HRM (crossvergence) in the Middle Eastern context. The analysis, based on the framework of cross-national HRM comparisons, helps to make both theoretical and practical implications

    Enhanced diagnostic yield in Meckel-Gruber and Joubert syndrome through exome sequencing supplemented with split-read mapping

    Get PDF
    Background The widespread adoption of high-throughput sequencing technologies by genetic diagnostic laboratories has enabled significant expansion of their testing portfolios. Rare autosomal recessive conditions have been a particular focus of many new services. Here we report a cohort of 26 patients referred for genetic analysis of Joubert (JBTS) and Meckel-Gruber (MKS) syndromes, two clinically and genetically heterogeneous neurodevelopmental conditions that define a phenotypic spectrum, with MKS at the severe end. Methods Exome sequencing was performed for all cases, using Agilent SureSelect v5 reagents and Illumina paired-end sequencing. For two cases medium-coverage (9×) whole genome sequencing was subsequently undertaken. Results Using a standard analysis pipeline for the detection of single nucleotide and small insertion or deletion variants, molecular diagnoses were confirmed in 12 cases (4 %). Seeking to determine whether our cohort harboured pathogenic copy number variants (CNV), in JBTS- or MKS-associated genes, targeted comparative read-depth analysis was performed using FishingCNV. These analyses identified a putative intragenic AHI1 deletion that included three exons spanning at least 3.4 kb and an intergenic MPP4 to TMEM237 deletion that included exons spanning at least 21.5 kb. Whole genome sequencing enabled confirmation of the deletion-containing alleles and precise characterisation of the mutation breakpoints at nucleotide resolution. These data were validated following development of PCR-based assays that could be subsequently used for “cascade” screening and/or prenatal diagnosis. Conclusions Our investigations expand the AHI1 and TMEM237 mutation spectrum and highlight the importance of performing CNV screening of disease-associated genes. We demonstrate a robust increasingly cost-effective CNV detection workflow that is applicable to all MKS/JBTS referrals
    corecore