Learning Bayesian Networks for Student Modeling

In the last decade, there has been a growing interest in using Bayesian Networks (BN) in the student modelling problem. This increased interest is probably due to the fact that BNs provide a sound methodology for this difficult task. In order to develop a Bayesian student model, it is necessary to define the structure (nodes and links) and the parameters. Usually the structure can be elicited with the help of human experts (teachers), but the difficulty of the problem of parameter specification is widely recognized in this and other domains. In the work presented here we have performed a set of experiments to compare the performance of two Bayesian Student Models, whose parameters have been specified by experts and learnt from data respectively. Results show that both models are able to provide reasonable estimations for knowledge variables in the student model, in spite of the small size of the dataset available for learning the parametersUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Screening a variable germplasm collection of Cucumis melo L. for seedling resistance to Macrophomina phaseolina

[EN] We evaluate the seedling resistance to charcoal rot caused by Macrophomina phaseolina in ninety-seven Cucumis melo accessions, from different geographical origins and five F1 generations, derived from crosses of five accessions selected for their resistance. Artificial inoculations with the toothpick method, previously reported to be useful for predicting shoot resistance, were performed, and plants were scored using a scale of disease severity. The average disease severity was calculated for each accession and was used to cluster the accession in five reaction classes. The screening revealed that sources of natural resistance to this fungus are limited. However, seedlings of seven accessions of different botanic groups displayed a resistant response to the stem inoculation, one cantaloup from Israel, one conomon accession from Korea, two wild agrestis and one acidulus from Africa, and two dudaim accessions from Middle East. The response of the F1 progenies varied from susceptibility to high resistance, the latter in progenies from the two agrestis wild types. These results suggest differences in the genetic basis of the resistance in the different selected sources. The resistant accessions are suggested to be screened under field conditions to confirm the level of resistance at adult plant stage and under stressful conditions.This work has been partially funded by the Project No 294/13 of the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior CAPES (Brazil). M. M. Q. Ambrosio and A. C. A. Dantas thank CAPES for their research fellowships. B.Pico thanks the Programa Hispano-Brasileno de Cooperacion Universitaria HBP2012-008 and PHBP14/00021 and to the MINECO project AGL2014-53398-C2-2-R.Ambrosio, MM.; Dantas, AC.; Martinez Perez, EM.; Medeiros, AC.; Sousa Nunes, GHD.; Picó Sirvent, MB. (2015). Screening a variable germplasm collection of Cucumis melo L. for seedling resistance to Macrophomina phaseolina. Euphytica. 206(2):287-300. https://doi.org/10.1007/s10681-015-1452-xS2873002062Aegerter BJ, Gordon TR, Davis RM (2000) Occurrence and pathogenicity of fungi associated with melon root rot and vine decline in California. Plant Dis 84:224–230Almeida AMR, Abdelnoor RV, Arias CAA, Carvalho VP, Jacoud Filho DS, Marin SRR, Benato LC, Pinto MC, Carvalho CGP (2003) Genotypic diversity among Brazilian isolates of Macrophomina phaseolina revealed by RAPD. Fitopatol Bras 28:279–285Almeida AMRA, Seixas CDSS, Farias JRBF, Oliveira MCN, Franchini JC, Debiasi H, Costa JM, Gaudêncio CA (2014) Macrophomina phaseolina em soja. Embrapa Soja, Londrina, p 30pAmbrósio MMQ, Bueno CJ, Padovani CR, Souza NL (2009) Sobrevivência de fungos fitopatogênicos habitantes do solo, em microcosmo, simulando solarização com prévia incorporação de materiais orgânicos. Summa Phytopathol 35(1):20–25Andrade DEGT, Michereff SJ, Biondi CM, Nascimento CWA, Sales R Jr (2005) Frequência de fungos associados ao colapso do meloeiro e relação com características físicas, químicas e microbiológicas dos solos. Summa Phytopathol 31(4):327–333Bedendo IP (2011) Podridões de raiz e de colo. In: Amorin L, Rezende JAM, Bergamin Filho A (eds) Manual de Fitopatologia: Princípios e conceitos. Agronômica Ceres, São Paulo, pp 443–448Bramel-Cox PJ, Stein IS, Rodgers DM, Claflin LE (1988) Inheritance of resistance to Macrophomina phaseolina (Tassi) Goid. and Fusarium moniliforme Sheldom in Sorghum. Crop Sci 28(1):37–40Bruton BD, Miller E (1997) Occurrence of vine decline diseases of melons in Honduras. Plant Dis 81(6):696Bruton BD, Jeger MD, Reuveni R (1987) Macrophomina phaseolina infection and vine decline in cantaloupe in relation to planting date, soil environment, and maturation. Plant Dis 71(3):259–263Burger Y, Katzir N, Tzuri G, Portnoy V, Saar U, Shriber S, Perl-Treves R, Cohen R (2003) Variation in the response of melon genotypes to Fusarium oxysporum f. sp. melonis race 1 determined by inoculation tests and molecular markers. Plant Pathol 52:204–211Chamorro M, Miranda L, Domínguez P, Medina JJ, Soria C, Romero F, López Aranda JM, De los Santos B (2015) Evaluation of biosolarization for the control of charcoal rot disease (Macrophomina phaseolina) in strawberry. Crop Prot 67:279–286Cohen R (1993) A leaf disk assay for detection of resistance of melons to Sphaerotheca fuliginea race 1. Plant Dis 77(5):513–517Cohen R, Katzir N, Schreiber S, Greenberg R (1996) Occurrence of Shaerotheca fuliginea Race 3 on Cucurbits in Israel. Plant Dis 80:334Cohen R, Omari N, Porat A, Edelstein M (2012) Management of Macrophomina wilt in melons using grafting or fungicide soil application: pathological, horticultural and economical aspects. Crop Prot 35:58–63Cohen R, Tyutyunik J, Fallik E, Oka Y, Tadmor Y, Edelstein M (2014) Phytopathological evaluation of exotic watermelon germplasm as a basic for rootstock breeding. Sci Hortic 165:203–210Dantas AMM, Ambrósio MMQ, Nascimento SRC, Senhor RF, Cézar MA, Lima JSS (2013) Incorporation of plant materials in the control of root pathogens in mushmelon. Revista Agro@ambiente on-line 7(3):338–344Davis RM, Turini TA, Aegerter BJ, Stapleton JJ (2009) Cucurbits charcoal rot, pathogen: Macrophomina phaseolina. UC IPM online. http://www.totoagriculture.org/PDFs/PlantDiseasesPests/1026.pdf . Accessed 25 Feb 2015Dias RCS, Picó B, Espinos A, Nuez F (2004) Resistance to melón vine decline derived from Cucumis melo ssp. agrestis: genetic analysis of root structure and root response. Plant Breed 123:66–72Diourte M, Starr JL, Jegger MJ, Stack JP, Rosenow DT (1995) Charcoal rot (Macrophomina phaseolina) resistance and the effect of water stress on disease development in Sorghum. Plant Pathol 44:196–202Esteras C, Pascual B, Nuez F, Picó MB (2009) Use of ecotilling to identify natural allelic variants of melon candidate genes involved in fuit ripening. 8th Plant Genomics European Meeting (Plant GEM 8) Istambul, 213Esteras C, Formisano G, Roig C, Díaz A, Blanca J, Garcia-Mas J, Gómez-Guillamón ML, López-Sesé AI, Lázaro A, Monforte AJ, Picó B (2013) SNP genotyping in melons: genetic variation, population structure, and linkage disequilibrium. Theor Appl Genet 126(5):1285–1303. doi: 10.1007/s00122-013-2053-5Fang X, Phillips D, Li H, Sivasithamparama K, Barbettia MJ (2011) Comparisons of virulence of pathogens associated with crown and root diseases of strawberry in Western Australia with special reference to the effect of temperature. Sci Hortic 131(22):39–48Food and Agriculture Organization (2014) Faostat. http://faostat.fao.org/site/567/default.aspx#ancor . Accessed 11 Nov 2011García-Jiménez J, Martínez-Ferrer G, Armengol J, Velazquez MT, Orts M, Juárez M, Ortega A, Jordá MC, Alfaro A (1993) Agentes asociados al colapso del melón en distintas zonas españolas. Bol San Veg Plagas 19:401–423Grezes-Besset B, Lucante N, Kelechian V, Dargent R, Muller H (1996) Evaluation of castor bean resistance to sclerotial wilt disease caused by Macrophomina phaseolina. Plant Dis 80(8):842–846Hutcheson SW (1998) Current concepts of active defense in plants. Annu Rev Phytopathol 36:59–90Iglesias A, Picó B, Nuez F (2000) A temporal genetic analysis of disease resistance genes resistance to melon vine decline derived from Cucumis melo var. agrestis. Plant Breed 119:329–334Islam MS, Haque MS, Islam MM, Emdad EM, Halim A, Hossen QMM, Hossain MZ, Ahmed B, Rahim S, Rahman MS, Alam MM, Hou S, Wan X, Saito JÁ, Alam M (2012) Tools to kill: genome of one of the most destructive plant pathogenic fungi Macrophomina phaseolina. BMC Genomic 13(493):1–16Jacob CJ, Krarup C, Díaz A, Latorre BA (2013) A severe outbreak of charcoal rot in cantaloupe melon caused by Macrophomina phaseolina in Chile. Plant Dis 97(1):141Kaur S, Dhillon GS, Brar SK, Vallad GE, Chand R, Chauhan VB (2012) Emerging phytopathogen Macrophomina phaseolina: biology, economic importance and current diagnostic trends. Crit Rev Microbiol 38(1):136–151Keeling A (1982) Seedling test for resistance to soybean stem canker caused by diaporthe phaseolorum var. caulivora. Phytopathology 72(7):807–809Khan SN (2007) Macrophomina phaseolina as causal agent for charcoal rot of sunflower. Mycopath 5(2):111–118Khan SH, Shuaib M (2007) Identification of sources of resistance in Mung bean (Vigna radiata L.) against Charcoal Rot Macrophomina phaseolina (Tassi) Goid. Afr Crop Sci 8:2101–2102Krikun J, Orion D, Nachmias A, Reuveni R (1982) The role of soilborne pathogens under conditions of intensive agricultura. Phytoparasitica 10(4):247–258Mahmoudi SB, Ghashghaie S (2013) Reaction of sugar beet S1 lines and cultivars to different isolates of Macrophomina phaseolina and Rhizoctonia solani AG-2-2IIIB. Euphytica 190:39–445. doi: 10.1007/s10681-012-0832-8Mertely J, Seijo T, Peres N (2005) First report of Macrophomina phaseolina causing a crown rot of strawberry in Florida. Plant Dis 89(4):434Mughogho LK, Pande S (1984) Charcoal Rot of Sorghum. In: Mughogho LK, Rosenberg G (eds) Sorghum root and stalk rots, a critical review: proceedings of the consultative group discussion on research needs and strategies for control of sorghum root and stalk rot diseases. Icrisat, Bellagio, pp 11–24Nischwitz C, Olsen M, Rasmussen S (2004) Effect of irrigation type on inoculum density of Macrophomina phaseolina in melon fields in Arizona. J Phytopathol 152(3):133–137Noling JW, Becker JO (1994) The challenge of research and extension to define and implement alternatives to methyl bromide. J Nematol 26(4S):573–586Pitrat M (2008) Melon. In: Prohens J, Nuez F (eds) Handbook of plant breeding. Springer, New York, pp 283–315Purkayastha S, Kaur B, Dilbaghi N, Chaudhury A (2006) Characterization of Macrophomina phaseolina, the charcoal rot pathogen of cluster bean, using conventional techniques and PCR-based molecular markers. Plant Pathol 55:106–116. doi: 10.1111/j.1365-3059.2005.01317.xRadwan O, Rouhana LV, Hartman GL, Korban SS (2014) Genetic mechanisms of host-pathogen interactions for charcoal rot in soybean. Plant Mol Biol Report 32(3):617–629Ravf BA, Ahmad I (1998) Studies on correlation of seed infection to field incidence of Alternaria alternate and Macrophomina phaseolina in Sunflower. 13th Iranian Plant Protection Congress-Karaj, p 113Roustaee A, Reyhan MK, Jafari M (2011) Study of interaction between salinity and charcoal rot diseases of melon (Macrophomina phaseolina) in Semnan and Garmsar. Desert 16(2):175–218Salari M, Panjehkeh N, Nasirpoor Z, Abkhoo J (2012) Reaction of melón (Cucumis melo L.) cultivars to soil-borne plant pathogenic fungi in Iran. Afr J Biotecnol 11(87):15324–15329Sales R Jr, Oliveira OF, Medeiros EV, Guimarães IM, Correia KC, Michereff SJ (2012) Ervas daninhas como hospedeiras alternativas de patógenos causadores do colapso do meloeiro. Rev Ciênc Agron 43(1):195–198Sas Institute (2000) Sas/Stat user´s guide: statistics, version 8.01, v. 2, 4. SAS Institute, Inc, CaryScandiani MM, Ruberti DS, Giorda LM, Pioli RN, Luque AG, Bottai H, Ivancovich JJ, Aoki T, O´Donnell K (2011) Comparison of inoculation methods for characterizing relative aggressiveness of two soybean sudden-death syndrome pathogens, Fusarium virguliforme and F. tucumaniae. Trop Plant Pathol 36(3):133–140Scott AJ, Knott MA (1974) Cluster analysis method for grouping means in the analysis of variance. Biometrics 30(3):507–512Sebastian P, Schaefer H, Telford IRH, Renner SS (2010) Cucumber (Cucumis sativus) and melon (C. melo) have numerous wild relatives in Asia and Australia, and the sister species of melon is from Australia. Proc Natl Acad Sci 107:14269–14273Sharmishtha P, Bhavneet K, Neeraj D, Ashok C (2006) Evaluation of cluster bean genotypes for resistance to charcoal rot caused by Macrophomina phaseolina using different host inoculation methods pages. J Crop Improv 15(1):67–79Shekhar M, Sharma RC, Singh L, Dutta R (2006) Morphological and pathogenic variability of Macrophomina phaseolina (Tassi.) Goid Incitant of charcoal rot of maize in India. Indian Phytopath 59(3):294–298Stapleton JJ (2000) Soil solarization in various agricultural production systems. Crop Prot 19:837–841Twizeyimana M, Hill CB, Pawlowski M, Paul C, Hartman GL (2012) A cut-stem inoculation technique to evaluate soybean for resistance to Macrophomina phaseolina. Plant Dis 96(8):1210–1215Watson A, Napier T (2009) Disease of cucurbit vegetables. Primefact 832:1–6Wolukau JN, Zhou XH, Li Y, Zhang Y, Chen J (2007) Resistance to gummy stem blight in melon (Cucumis melo L.) germplasm and inheritance of resistance from plant introductions 157076, 420145, and 323498. HortScience 42(2):215–221Wrather JA, Anderson TR, Arsyad DM, Tan Y, Ploper LD, Porta-Puglia A, Ram HH, Yorinori JT (2001) Soybean disease loss estimates for the top ten soybean-producing countries in 1998. Can J Plant Pathol 23:115–12

Using machine learning techniques for architectural design tracking: An experimental study of the design of a shelter

In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on the quality of the final project and to find and assess common solution pathways in problem-solving behaviour. In this sense, we propose a new methodology for design tracking, based on the application of data analysis and machine learning techniques to data obtained in snapshots of selected design instants. This methodology has been applied in an experimental study, in which fifty-two novice designers were required to design a shelter with the help of a specifically developed computer tool that allowed collecting snapshots of the project at six selected design instants. The snapshots were described according to nine variables. Data analysis and machine learning techniques were then used to extract the knowledge contained in the data. More concretely, supervised learning techniques (decision trees) were used to find strategies employed in higher-quality designs, while unsupervised learning techniques (clustering) were used to find common solution pathways. Results provide evidence that supervised learning techniques allow elucidating the class of the best projects by considering the order of some of the decisions taken. Also, unsupervised learning techniques can find several common problem-solving pathways by grouping projects into clusters that use similar strategies. In this way, our work suggests a novel approach to design tracking, using quantitative analysis methods that can complement and enrich the traditional qualitative approachThis work has been partially funded by the Spanish Government, Agencia Estatal de Investigación (AEI), and the European Union, Fondo Europeo de Desarrollo Regional (FEDER), grant TIN2016-80774-R (AEI/FEDER, UE). Funding for open access charge: Universidad de Málaga/CBUA

Using machine learning techniques for architectural design tracking: an experimental study of the design of a shelter

In this paper, we present a study aimed at tracking and analysing the design process. More concretely, we intend to explore whether some elements of the conceptual design stage in architecture might have an influence on the quality of the final project and to find and assess common solution pathways in problem-solving behaviour. In this sense, we propose a new methodology for design tracking, based on the application of data analysis and machine learning techniques to data obtained in snapshots of selected design instants. This methodology has been applied in an experimental study, in which fifty-two novice designers were required to design a shelter with the help of a specifically developed computer tool that allowed collecting snapshots of the project at six selected design instants. The snapshots were described according to nine variables. Data analysis and machine learning techniques were then used to extract the knowledge contained in the data. More concretely, supervised learning techniques (decision trees) were used to find strategies employed in higher-quality designs, while unsupervised learning techniques (clustering) were used to find common solution pathways. Results provide evidence that supervised learning techniques allow elucidating the class of the best projects by considering the order of some of the decisions taken. Also, unsupervised learning techniques can find several common problem-solving pathways by grouping projects into clusters that use similar strategies. In this way, our work suggests a novel approach to design tracking, using quantitative analysis methods that can complement and enrich the traditional qualitative approach.This work has been partially funded by the Spanish Government, Agencia Estatal de Investigaci ́on (AEI), and the European Union, Fondo Europeo de Desarrollo Regional (FEDER), grant TIN2016-80774-R (AEI/FEDER, UE). Funding for open access charge: Universidad de Málaga/CBUA

Spanish version of the Dundee Ready Education Environment Measure (DREEM) applied to undergraduate physical therapy students in Spain using Google Form

[Intro] The educational climate (EC) is an important factor in determining the effectiveness and success of the curriculum in a school of medical sciences. The Dundee Ready Education Environment Measure (DREEM) questionnaire was used to assess EC in a competency-based curriculum in the physical therapy program analyzing the mean total, subscale, and item scores, as well as response rates. To carry out a psychometric evaluation of the Spanish-language version of the DREEM applied to undergraduate physical therapy students, a total of 671 students enrolled on Degrees in Physiotherapy at 22 faculties across public and private universities in Spainresponded to the DREEM questionnaire using Google Form. (...

Response to Bile Salts in Clinical Strains of Acinetobacter baumannii Lacking the AdeABC Efflux Pump: Virulence Associated with Quorum Sensing

Introduction:Acinetobacter baumannii is an opportunistic nosocomial pathogen associated with multiple infections. This pathogen usually colonizes (first stage of microbial infection) host tissues that are in contact with the external environment. As one of the sites of entry in human hosts is the gastrointestinal tract, the pathogen must be capable of tolerating bile salts. However, studies analyzing the molecular characteristics involved in the response to bile salts in clinical strains of A. baumannii are scarce.Material and Methods: Microbiological and transcriptional studies (arrays and RT-PCR) in the response to bile salts were carried out in isogenic (A. baumanni ΔadeB ATCC 17978 and A. baumannii ΔadeL ATCC 17978) and clinical strains from clone ST79/PFGE-HUI-1 which is characterized by lacking the AdeABC efflux pump and by overexpression the AdeFGH efflux pump.Results and Discussion: In presence of bile salts, in addition to the glutamate/aspartate transporter were found overexpressed in A. baumannii ΔadeB ATCC 17978, the virulence factors (surface motility, biofilm, and Type VI Secretion System) which are associated with activation of the Quorum Sensing system. Overexpression of these factors was confirmed in clinical strains of clone ST79/PFGE-HUI-1.Conclusions: This the first study about the adaptive response to bile salts investigating the molecular and microbiological characteristics in response to bile salts of an isogenic model of A. baumannii ATCC 17978 and clinical isolates of A. baumannii (clinical strains of ST79/PFGE-HUI-1) lacking the main RND efflux pump (AdeABC). Clinical isolates of A. baumannii lacking the AdeABC efflux pump (clone ST79/PFGE-HUI-1) displayed a new clinical profile (increased invasiveness) possibly associated with the response to stress conditions (such as the presence of bile salts)

A novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia

A high proportion of patients with acute myeloid leukemia who achieve minimal residual disease negative status ultimately relapse because a fraction of pathological clones remains undetected by standard methods. We designed and validated a high-throughput sequencing method for minimal residual disease assessment of cell clonotypes with mutations of NPM1, IDH1/2 and/or FLT3-single nucleotide variants. For clinical validation, 106 follow-up samples from 63 patients in complete remission were studied by sequencing, evaluating the level of mutations detected at diagnosis. The predictive value of minimal residual disease status by sequencing, multiparameter flow cytometry, or quantitative polymerase chain reaction analysis was determined by survival analysis. The sequencing method achieved a sensitivity of 10-4 for single nucleotide variants and 10-5 for insertions/deletions and could be used in acute myeloid leukemia patients who carry any mutation (86% in our diagnostic data set). Sequencing-determined minimal residual disease positive status was associated with lower disease-free survival (hazard ratio 3.4, P=0.005) and lower overall survival (hazard ratio 4.2, P<0.001). Multivariate analysis showed that minimal residual disease positive status determined by sequencing was an independent factor associated with risk of death (hazard ratio 4.54, P=0.005) and the only independent factor conferring risk of relapse (hazard ratio 3.76, P=0.012). This sequencing-based method simplifies and standardizes minimal residual disease evaluation, with high applicability in acute myeloid leukemia. It is also an improvement upon flow cytometry- and quantitative polymerase chain reaction-based prediction of outcomes of patients with acute myeloid leukemia and could be incorporated in clinical settings and clinical trials.This study was supported by the Subdirección General de Investigación Sanitaria (Instituto de Salud Carlos III, Spain) grants PI13/02387 and PI16/01530, and the CRIS against Cancer foundation grant 2014/0120. ML holds a postdoctoral fellowship of the Spanish Ministry of Economy and Competitiveness (FPDI-2013- 16409). PRP holds a postdoctoral fellowship of the Spanish Instituto de Salud Carlos III: Contrato Predoctoral de Formación en Investigación en Salud i-PFIS (IFI 14/00008).S

Novel deep targeted sequencing method for minimal residual disease monitoring in acute myeloid leukemia

A high proportion of patients with acute myeloid leukemia who achieve minimal residual disease (MRD) negative status ultimately relapse because a fraction of pathological clones remains undetected by standard methods. We designed and validated a high-throughput sequencing method for MRD assessment of cell clonotypes with mutations of NPM1, IDH1/2 and/or FLT3-SNVs. For clinical validation, 106 follow-up samples from 63 patients in complete remission were studied by NGS, evaluating the level of mutations detected at diagnosis. The predictive value of MRD status by NGS, multiparameter flow cytometry, or quantitative PCR was determined by survival analysis. The method achieved a sensitivity of 10-4 for SNV mutations and 10-5 for insertions/deletions and could be used in acute myeloid leukemia patients who carry any mutation (86% in our diagnosis data set). NGS-determined MRD positive status was associated with lower disease-free survival (hazard ratio [HR] 3.4, p=0.005) and lower overall survival (HR 4.2, p<0.001). Multivariate analysis showed that MRD positive status by NGS was an independent factor associated with risk of death (HR 4.54, p =0.005) and the only independent factor conferring risk of relapse (HR 3.76, p =0.012). This NGS based method simplifies and standardizes MRD evaluation, with high applicability in acute myeloid leukemia. It also improves upon flow cytometry and quantitative PCR to predict acute myeloid leukemia outcome and could be incorporated in clinical settings and clinical trials.This study was supported by the Subdirección General de Investigación Sanitaria (Instituto de Salud Carlos III, Spain) grants PI13/02387 and PI16/01530, and the CRIS against Cancer foundation grant 2014/0120. M.L. holds a postdoctoral fellowship of the Spanish Ministry of Economy and Competitiveness (FPDI-2013-16409). P.R.P. holds a postdoctoral fellowship of the Spanish of Instituto de Salud Carlos III: Contrato Predoctoral de Formación en Investigación en Salud i-PFIS (IFI 14/00008).S

Obstetric outcomes of sars-cov-2 infection in asymptomatic pregnant women

Altres ajuts: Fondo Europeo de Desarrollo Regional (FEDER)Around two percent of asymptomatic women in labor test positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Spain. Families and care providers face childbirth with uncertainty. We determined if SARS-CoV-2 infection at delivery among asymptomatic mothers had different obstetric outcomes compared to negative patients. This was a multicenter prospective study based on universal antenatal screening for SARS-CoV-2 infection. A total of 42 hospitals tested women admitted for delivery using polymerase chain reaction, from March to May 2020. We included positive mothers and a sample of negative mothers asymptomatic throughout the antenatal period, with 6-week postpartum follow-up. Association between SARS-CoV-2 and obstetric outcomes was evaluated by multivariate logistic regression analyses. In total, 174 asymptomatic SARS-CoV-2 positive pregnancies were compared with 430 asymptomatic negative pregnancies. No differences were observed between both groups in key maternal and neonatal outcomes at delivery and follow-up, with the exception of prelabor rupture of membranes at term (adjusted odds ratio 1.88, 95% confidence interval 1.13-3.11; p = 0.015). Asymptomatic SARS-CoV-2 positive mothers have higher odds of prelabor rupture of membranes at term, without an increase in perinatal complications, compared to negative mothers. Pregnant women testing positive for SARS-CoV-2 at admission for delivery should be reassured by their healthcare workers in the absence of symptoms