Impact d’une infection intra-mammaire causée par Staphylococcus aureus ou un staphylocoque coagulase-négative présente en début de lactation chez les taures laitières

L’objectif de cette étude était de déterminer l’impact d’une infection intra-mammaire (IIM) subclinique causée par staphylocoque coagulase-négative (SCN) ou Staphylococcus aureus diagnostiquée durant le premier mois de lactation chez les taures sur le comptage de cellules somatiques (CCS), la production laitière et le risque de réforme durant la lactation en cours. Des données bactériologiques provenant d’échantillons de lait composites de 2 273 taures Holstein parmi 50 troupeaux ont été interprétées selon les recommandations du National Mastitis Council. Parmi 1 691 taures rencontrant les critères de sélection, 90 (5%) étaient positives à S. aureus, 168 (10%) étaient positives à SCN et 153 (9%) étaient négatives (aucun agent pathogène isolé). Le CCS transformé en logarithme népérien (lnCCS) a été modélisé via une régression linéaire avec le troupeau comme effet aléatoire. Le lnCCS chez les groupes S. aureus et SCN était significativement plus élevé que dans le groupe témoin de 40 à 300 jours en lait (JEL) (P < 0.0001 pour tous les contrastes). La valeur journalière du lnSCC chez les groupes S. aureus et SCN était en moyenne 1.2 et 0.6 plus élevé que le groupe témoin respectivement. Un modèle similaire a été réalisé pour la production laitière avec l’âge au vêlage, le trait génétique lié aux parents pour la production laitière et le logarithme népérien du JEL de la pesée inclus. La production laitière n’était pas statistiquement différente entre les 3 groupes de culture de 40 à 300 JEL (P ≥ 0.12). Les modèles de survie de Cox ont révélé que le risque de réforme n’était pas statistiquement différent entre le groupe S. aureus ou SCN et le groupe témoin (P ≥ 0.16). La prévention des IIM causées par SCN et S. aureus en début de lactation demeure importante étant donné leur association avec le CCS durant la lactation en cours.

Facteurs de risque modifiables associés à l’incidence, l’élimination et la prévalence d’infections intra-mammaires chez la vache laitière en lactation

La mammite subclinique est un problème de santé fréquent et coûteux. Les infections intra-mammaires (IIM) sont souvent détectées à l’aide de mesures du comptage des cellules somatiques (CCS). La culture bactériologique du lait est cependant requise afin d’identifier le pathogène en cause. À cause de cette difficulté, pratiquement toutes les recherches sur la mammite subclinique ont été centrées sur la prévalence d’IIM et les facteurs de risque pour l’incidence ou l’élimination des IIM sont peu connus. L’objectif principal de cette thèse était d’identifier les facteurs de risque modifiables associés à l’incidence, l’élimination et la prévalence d’IIM d’importance dans les troupeaux laitiers Canadiens. En premier lieu, une revue systématique de la littérature sur les associations entre pratiques utilisées à la ferme et CCS a été réalisée. Les pratiques de gestion constamment associées au CCS ont été identifiées et différentiées de celles faisant l’objet de rapports anecdotiques. Par la suite, un questionnaire bilingue a été développé, validé, et utilisé afin de mesurer les pratiques de gestion d’un échantillon de 90 troupeaux laitiers canadiens. Afin de valider l’outil, des mesures de répétabilité et de validité des items composant le questionnaire ont été analysées et une évaluation de l’équivalence des versions anglaise et française a été réalisée. Ces analyses ont permis d’identifier des items problématiques qui ont du être recatégorisés, lorsque possible, ou exclus des analyses subséquentes pour assurer une certaine qualité des données. La plupart des troupeaux étudiés utilisaient déjà la désinfection post-traite des trayons et le traitement universel des vaches au tarissement, mais beaucoup des pratiques recommandées n’étaient que peu utilisées. Ensuite, les facteurs de risque modifiables associés à l’incidence, à l’élimination et à la prévalence d’IIM à Staphylococcus aureus ont été investigués de manière longitudinale sur les 90 troupeaux sélectionnés. L’incidence d’IIM semblait être un déterminant plus important de la prévalence d’IIM du troupeau comparativement à l’élimination des IIM. Le port de gants durant la traite, la désinfection pré-traite des trayons, de même qu’une condition adéquate des bouts de trayons démontraient des associations désirables avec les différentes mesures d’IIM. Ces résultats viennent souligner l’importance des procédures de traite pour l’obtention d’une réduction à long-terme de la prévalence d’IIM. Finalement, les facteurs de risque modifiables associés à l’incidence, à l’élimination et à la prévalence d’IIM à staphylocoques coagulase-négatif (SCN) ont été étudiés de manière similaire. Cependant, afin de prendre en considération les limitations de la culture bactériologique du lait pour l’identification des IIM causées par ce groupe de pathogènes, une approche semi-Bayesienne à l’aide de modèles de variable à classe latente a été utilisée. Les estimés non-ajusté de l’incidence, de l’élimination, de la prévalence et des associations avec les expositions apparaissaient tous considérablement biaisés par les imperfections de la procédure diagnostique. Ce biais était en général vers la valeur nulle. Encore une fois, l’incidence d’IIM était le principal déterminant de la prévalence d’IIM des troupeaux. Les litières de sable et de produits du bois, de même que l’accès au pâturage étaient associés à une incidence et une prévalence plus basse de SCN.

Scoliosis curve type classification from 3D trunk image

Adolescent idiopathic scoliosis (AIS) is a deformity of the spine manifested by asymmetry and deformities of the external surface of the trunk. Classification of scoliosis deformities according to curve type is used to plan management of scoliosis patients. Currently, scoliosis curve type is determined based on X-ray exam. However, cumulative exposure to X-rays radiation significantly increases the risk for certain cancer. In this paper, we propose a robust system that can classify the scoliosis curve type from non invasive acquisition of 3D trunk surface of the patients. The 3D image of the trunk is divided into patches and local geometric descriptors characterizing the surface of the back are computed from each patch and forming the features. We perform the reduction of the dimensionality by using Principal Component Analysis and 53 components were retained. In this work a multi-class classifier is built with Least-squares support vector machine (LS-SVM) which is a kernel classifier. For this study, a new kernel was designed in order to achieve a robust classifier in comparison with polynomial and Gaussian kernel. The proposed system was validated using data of 103 patients with different scoliosis curve types diagnosed and classified by an orthopedic surgeon from the X-ray images. The average rate of successful classification was 93.3% with a better rate of prediction for the major thoracic and lumbar/thoracolumbar types.

Non invasive classification system of scoliosis curve types using least-squares support vector machines

Objective To determine scoliosis curve types using non invasive surface acquisition, without prior knowledge from X-ray data. Methods Classification of scoliosis deformities according to curve type is used in the clinical management of scoliotic patients. In this work, we propose a robust system that can determine the scoliosis curve type from non invasive acquisition of the 3D back surface of the patients. The 3D image of the surface of the trunk is divided into patches and local geometric descriptors characterizing the back surface are computed from each patch and constitute the features. We reduce the dimensionality by using principal component analysis and retain 53 components using an overlap criterion combined with the total variance in the observed variables. In this work, a multi-class classifier is built with least-squares support vector machines (LS-SVM). The original LS-SVM formulation was modified by weighting the positive and negative samples differently and a new kernel was designed in order to achieve a robust classifier. The proposed system is validated using data from 165 patients with different scoliosis curve types. The results of our non invasive classification were compared with those obtained by an expert using X-ray images. Results The average rate of successful classification was computed using a leave-one-out cross-validation procedure. The overall accuracy of the system was 95%. As for the correct classification rates per class, we obtained 96%, 84% and 97% for the thoracic, double major and lumbar/thoracolumbar curve types, respectively. Conclusion This study shows that it is possible to find a relationship between the internal deformity and the back surface deformity in scoliosis with machine learning methods. The proposed system uses non invasive surface acquisition, which is safe for the patient as it involves no radiation. Also, the design of a specific kernel improved classification performance.

Prediction of scoliosis curve type based on the analysis of trunk surface topography

Scoliosis treatment strategy is generally chosen according to the severity and type of the spinal curve. Currently, the curve type is determined from X-rays whose acquisition can be harmful for the patient. We propose in this paper a system that can predict the scoliosis curve type based on the analysis of the surface of the trunk. The latter is acquired and reconstructed in 3D using a non invasive multi-head digitizing system. The deformity is described by the back surface rotation, measured on several cross-sections of the trunk. A classifier composed of three support vector machines was trained and tested using the data of 97 patients with scoliosis. A prediction rate of 72.2% was obtained, showing that the use of the trunk surface for a high-level scoliosis classification is feasible and promising.

Feature Point Detection and Curve Approximation for Early Processing of Freehand Sketches

Freehand sketching is both a natural and crucial part of design, yet is unsupported by current design automation software. We are working to combine the flexibility and ease of use of paper and pencil with the processing power of a computer to produce a design environment that feels as natural as paper, yet is considerably smarter. One of the most basic steps in accomplishing this is converting the original digitized pen strokes in the sketch into the intended geometric objects using feature point detection and approximation. We demonstrate how multiple sources of information can be combined for feature detection in strokes and apply this technique using two approaches to signal processing, one using simple average based thresholding and a second using scale space.

Predicting random level and seasonality of hotel prices. A structural equation growth curve approach

This article examines the effect on price of different characteristics of holiday hotels in the sun-and-beach segment, under the hedonic function perspective. Monthly prices of the majority of hotels in the Spanish continental Mediterranean coast are gathered from May to October 1999 from the tour operator catalogues. Hedonic functions are specified as random-effect models and parametrized as structural equation models with two latent variables, a random peak season price and a random width of seasonal fluctuations. Characteristics of the hotel and the region where they are located are used as predictors of both latent variables. Besides hotel category, region, distance to the beach, availability of parking place and room equipment have an effect on peak price and also on seasonality. 3- star hotels have the highest seasonality and hotels located in the southern regions the lowest, which could be explained by a warmer climate in autumn

The crime kuznets curve

We document the existence of a Crime Kuznets Curve in US states since the 1970s. As income levels have risen, crime has followed an inverted U-shaped pattern, first increasing and then dropping. The Crime Kuznets Curve is not explained by income inequality. In fact, we show that during the sample period inequality has risen monotonically with income, ruling out the traditional Kuznets Curve. Our finding is robust to adding a large set of controls that are used in the literature to explain the incidence of crime, as well as to controlling for state and year fixed effects. The Curve is also revealed in nonparametric specifications. The Crime Kuznets Curve exists for property crime and for some categories of violent crime.

Splanchnic metabolism of dairy cows during the transition from late gestation through early lactation

Blood flow and net nutrient fluxes for portal-drained viscera (PDV) and liver ( total splanchnic tissues) were measured at 19 and 9 d prepartum and at 11, 21, 33, and 83 d in milk ( DIM) in 5 multiparous Holstein-Friesian cows. Cows were fed a grass silage-based gestation ration initially and a corn silage-based lactation ration peripartum and postpartum. Meals were fed at 8-h intervals and hourly (n = 8) measures of splanchnic metabolism were started before ( 0730 h and 0830 h) feeding at 0830 h. Dry matter intakes (DMI) at 19 and 9 d prepartum were not different. Metabolism changes measured from 19 to 9 d prepartum were lower arterial insulin and acetate, higher arterial nonesterified fatty acids and increased net liver removal of glycerol. After calving, PDV and liver blood flow and oxygen consumption more than doubled as DMI and milk yield increased, but 85 and 93% of the respective increases in PDV and liver blood flow at 83 DIM had occurred by 11 DIM. Therefore, factors additional to DMI must also contribute to increased blood flow in early lactation. Most postpartum changes in net PDV and liver metabolism could be attributed to increases in DMI and digestion or increased milk yield and tissue energy loss. Glucose release was increasingly greater than calculated requirements as DIM increased, presumably as tissue energy balance increased. Potential contributions of lactate, alanine, and glycerol to liver glucose synthesis were greatest at 11 DIM but decreased by 83 DIM. Excluding alanine, there was no evidence of an increased contribution of amino acids to liver glucose synthesis is required in early lactation. Increased net liver removal of propionate (69%), lactate (20%), alanine (8%), and glycerol (4%) can account for increased liver glucose release in transition cows from 9 d before to 11 d after calving.

Visceral tissue mass and rumen volume in dairy cows during the transition from late gestation to early lactation

The objectives were to measure the effects of transition and supplemental barley or rumen-protected protein on visceral tissue mass in dairy cows and the effects of transition and barley on rumen volume and liquid turnover. Cows were individually fed a grass silage-based gestation ration to meet energy and protein requirements for body weight stasis beginning 6 wk before expected calving. A corn silage-based lactation ration was individually fed ad libitum after calving. In the visceral mass study, 36 cows were randomly assigned to one of 3 dietary treatments: basal ration or basal ration plus either 800 g dry matter (DM) of barley meal per day or 750 g DM of rumen-protected soybean protein per day. Cows were slaughtered at 21 and 7 d before expected calving date or at 10 and 22 d postpartum. Visceral mass and rumen papillae characteristics were measured. Diets had little effect on visceral mass. The mass of the reticulo-rumen, small intestine, large intestine, and liver was, or tended to be, greater at 22 d postpartum but not at 10 d postpartum before DM intake had increased. Rumen papillae mass increased at 10 d postpartum, perhaps in response to increased concentrates. Mesenteric fat decreased after calving, reflecting body fat mobilization. Ten rumen-cannulated cows were fed the basal gestation ration alone or supplemented with 880 g of barley meal DM. Rumen volumes and liquid dilution rates were measured at 17 and 8 d before calving and at 10, 20, and 31 d postpartum. Feeding barley had no effects. After calving, rumen DM volume and liquid dilution rate increased, but liquid volume did not increase. Changes in gastrointestinal and liver mass during transition were apparently a consequence of changes in DM intake and nutrient supply and not initiation of lactation per se.

Metabolic profiles and progesterone cycles in first lactation dairy cows

This study investigated the ovarian function, metabolic profiles and fertility in first lactation Holstein-Friesian dairy cows (mean 305 day milk yield: 7417 +/- 191 kg, n = 37). Reproductive profiles obtained from milk progesterone analysis were categorized into normal (n = 17) and four abnormal profiles (delayed ovulation, DOV1, n = 9; DOV2, n = 2; persistent corpus luteum, PCL1, n = 6; PCL2, n = 4; 1: immediately post-calving, 2: subsequent cycles). Fifty-five percent of cows had abnormal profiles with half of these being categorized as DOV1. Fertility of DOV1 and DOV2 cows was reduced whereas PCL1 and PCL2 cows had similar reproductive competence to normal profile cows. DOV1 animals had higher milk energy values, lower energy balances, lower dry matter intakes (DMI) and greater body weight and body condition score (BCS) losses post-calving than normal profile animals. DOV1 animals also had lower insulin-like growth factor-I (IGF-I) and higher betahydroxybutyrate (BHB) concentrations and tended to have the lower insulin and glucose concentrations in the pre-service period than normal profile cows. All PCL animals had vulval discharges postpartum. Despite this, the DMI, body weight and BCS changes, IGF-I concentrations and fertility of PCL1 animals was similar to normal profile cows. In conclusion, the high prevalence of delayed ovulation post-calving (DOV1) in primiparous high yielding cows lasted long enough (71 +/- 8.3 days) to have a detrimental impact on fertility and was associated with significant physiological changes. This study did not establish any detrimental effects of PCL profiles on fertility or production parameters. (C) 2002 Elsevier Science Inc. All rights reserved.