A Comparison Efficacy Study of Commercial Nasopharyngeal Swabs versus a Novel 3D Printed Swab for the Detection of SARS-CoV-2

The large volume of diagnostic tests required by the response to the pandemic of COVID-19 pandemic resulted in a shortage of commercial nasopharyngeal swabs. In an effort to alleviate the shortage, swabs created by 3D printing may be a solution. We designed and produced 3D printed swabs and sought to compare their ability to detect SARS-CoV-2 in patients admitted for COVID-19 or who were suspected of having COVID-19. A total of 30 patients were swabbed with a commercial and printed 3D swab. Results matched in 28 of 31 patients (90%). Two patients were discordant with a positive commercial swab and a negative 3D printed swab and another was discordant because the 3D printed swab was positive and the commercial swab was negative. The sensitivity was 89%, specificity was 92% and Cohen’s kappa coefficient was 0.80. The 3D printed swabs performed acceptably compared to the commercial swab and may be considered for use in lieu of a commercial swab

Cloning, characterization and immunolocalization of human ameloblastin

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/93555/1/j.1600-0722.2000.108004303.x.pd

MODULATION IN VITRO DU PHENOTYPE CHONDROCYTAIRE ET OSTEOBLASTIQUE EN REPONSE A L'INDUCTION PAR LES BONE MORPHOGENETIC PROTEIN -2 ET -4

PARIS7-Odontologie (751062104) / SudocPARIS-BIUM (751062103) / SudocCentre Technique Livre Ens. Sup. (774682301) / SudocSudocFranceF

Expression de la réponse glycogénique à l'insuline dans les hépatocytes fœtaux en culture

International audienc

Le quartier antique de la Grande-Boissière à Jublains (Mayenne)

Abstract ; Since the 18th century, there has been much research on the Antique town of Jublains - Nouiodunum, former capital ofthe Aulerci Diablinti. In 1996, a communal project provided the opportunity to study a new sector ofabout 4,400 sq. m. in the south-eastern part ofthe Antique town. The excavations provided some evidence of La Tène occupation and diffuse hints of the Augustan period, but true urbanization ofthe area appears only during Tibero-Claudian times. Nevertheless, it remained on hold : streets unfinished and residential allotment incomplete. Workshop units (forges, tannery) settle in the spaces remaining vacant, before a progressive desertion takes place between the end of IInd and IIIrd centuries. A real reappropriation of the area is not detectable before the VIIIth - IXth centuries. Concordance of building orientations between this period and Antiquity questions the reality and significance of this observed apparent hiatus, aboutfive centuries long.Depuis le 18e siècle, de nombreux travaux ont concerné l'agglomération antique de Jublains - Nouiodunum, ancien chef-lieu des Aulerques Diablintes. En 1996, un projet communal a fourni l'occasion d'étudier un nouveau secteur de quelque 4 400 m2 dans la partie sud-est de la ville antique. Les fouilles ont livré quelques traces d'une occupation laténienne et des indices diffus de l'époque augustéenne mais la véritable urbanisation du quartier n'intervient qu'à la période tibéro-claudienne. Celle-ci est toutefois restée en suspens : réseau viaire inachevé et implantation résidentielle incomplète. Les espaces incomplètement aménagés sont occupés par des unités artisanales (forges, tannerie), avant qu'un abandon progressif du quartier n'intervienne entre la fin du IIe siècle et celle du IIIe. Une véritable réappropriation des lieux ne s'observe qu'aux VIIIe - IXe siècles. La concordance des orientations entre le bâti de cette époque et celui de l'Antiquité pose question quant à la réalité et à la nature de ce hiatus apparent de près de cinq siècles.Bocquet Anne, Chuniaud Kristell, Naveau Jacques, Dieudonné-Glad Nadine, Forest Vianney, Morin Sylvaine, Mortreau Maxime. Le quartier antique de la Grande-Boissière à Jublains (Mayenne). In: Revue archéologique de l'ouest, tome 21, 2004. pp. 131-174

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

12 p.International audienceBackground: The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods: A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results: The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]). The deterministic transmission model, with stochastic environmental factor, predicted an endemoepidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Conclusion: Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Nonlinear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation

Modelling malaria incidence with environmental dependency in a locality of Sudanese savannah area, Mali

Abstract Background The risk of Plasmodium falciparum infection is variable over space and time and this variability is related to environmental variability. Environmental factors affect the biological cycle of both vector and parasite. Despite this strong relationship, environmental effects have rarely been included in malaria transmission models. Remote sensing data on environment were incorporated into a temporal model of the transmission, to forecast the evolution of malaria epidemiology, in a locality of Sudanese savannah area. Methods A dynamic cohort was constituted in June 1996 and followed up until June 2001 in the locality of Bancoumana, Mali. The 15-day composite vegetation index (NDVI), issued from satellite imagery series (NOAA) from July 1981 to December 2006, was used as remote sensing data. The statistical relationship between NDVI and incidence of P. falciparum infection was assessed by ARIMA analysis. ROC analysis provided an NDVI value for the prediction of an increase in incidence of parasitaemia. Malaria transmission was modelled using an SIRS-type model, adapted to Bancoumana's data. Environmental factors influenced vector mortality and aggressiveness, as well as length of the gonotrophic cycle. NDVI observations from 1981 to 2001 were used for the simulation of the extrinsic variable of a hidden Markov chain model. Observations from 2002 to 2006 served as external validation. Results The seasonal pattern of P. falciparum incidence was significantly explained by NDVI, with a delay of 15 days (p = 0.001). An NDVI threshold of 0.361 (p = 0.007) provided a Diagnostic Odd Ratio (DOR) of 2.64 (CI95% [1.26;5.52]). The deterministic transmission model, with stochastic environmental factor, predicted an endemo-epidemic pattern of malaria infection. The incidences of parasitaemia were adequately modelled, using the observed NDVI as well as the NDVI simulations. Transmission pattern have been modelled and observed values were adequately predicted. The error parameters have shown the smallest values for a monthly model of environmental changes. Conclusion Remote-sensed data were coupled with field study data in order to drive a malaria transmission model. Several studies have shown that the NDVI presents significant correlations with climate variables, such as precipitations particularly in Sudanese savannah environments. Non-linear model combining environmental variables, predisposition factors and transmission pattern can be used for community level risk evaluation.</p