The development of the passé composé in lower-intermediate learners of French as a second language

In this study we tracked the development of the passe compose in second-language learners of French whose first language is English. Although the passe compose is a highly used tense among native speakers of French and it appears to present particular difficulty for first-language English speakers, its second-language development has been surprisingly under-researched. In order to trace developmental patterns of the passe compose we obtained a corpus of obligatory context use of this tense by 30 Year-12 (lower-intermediate) students at two time points six months apart and analysed the data both quantitatively and qualitatively. Our findings suggest that these students used remarkably few memorized formulas, that they passed through five distinct stages in their acquisition of the passe compose, that those early stages were characterized by transfer errors, and that the presence of the auxiliary, whether correct or incorrect, formed a crucial stage in the development of the tense. Theoretical explanations for the findings are presented together with some tentative pedagogical implications

An institute for enhancing effective environmental adjudication

Texto de autoria de Ministro do Superior Tribunal de Justiça

Gene expression markers of tendon fibroblasts in normal and diseased tissue compared to monolayer and three dimensional culture systems

<p>Abstract</p> <p>Background</p> <p>There is a paucity of data regarding molecular markers that identify the phenotype of the tendon cell. This study aims to quantify gene expression markers that distinguish between tendon fibroblasts and other mesenchymal cells which may be used to investigate tenogenesis.</p> <p>Methods</p> <p>Expression levels for 12 genes representative of musculoskeletal tissues, including the proposed tendon progenitor marker scleraxis, relative to validated reference genes, were evaluated in matched samples of equine tendon (harvested from the superficial digital flexor tendon), cartilage and bone using quantitative PCR (qPCR). Expression levels of genes associated with tendon phenotype were then evaluated in healthy, including developmental, and diseased equine tendon tissue and in tendon fibroblasts maintained in both monolayer culture and in three dimensional (3D) collagen gels.</p> <p>Results</p> <p>Significantly increased expression of scleraxis was found in tendon compared with bone (P = 0.002) but not compared to cartilage. High levels of COL1A2 and scleraxis and low levels of tenascin-C were found to be most representative of adult tensional tendon phenotype. While, relative expression of scleraxis in developing mid-gestational tendon or in acute or chronically diseased tendon did not differ significantly from normal adult tendon, tenascin-C message was significantly upregulated in acutely injured equine tendon (P = 0.001). Relative scleraxis gene expression levels in tendon cell monolayer and 3D cultures were significantly lower than in normal adult tendon (P = 0.002, P = 0.02 respectively).</p> <p>Conclusion</p> <p>The findings of this study indicate that high expression of both COL1A2 and scleraxis, and low expression of tenascin-C is representative of a tensional tendon phenotype. The <it>in vitro </it>culture methods used in these experiments however, may not recapitulate the phenotype of normal tensional tendon fibroblasts in tissues as evidenced by gene expression.</p

Implementation and evaluation of a harm-reduction model for clinical care of substance using pregnant women

<p>Abstract</p> <p>Background</p> <p>Methamphetamine (MA) use during pregnancy is associated with many pregnancy complications, including preterm birth, small for gestational age, preeclampsia, and abruption. Hawaii has lead the nation in MA use for many years, yet prior to 2007, did not have a comprehensive plan to care for pregnant substance-using women. In 2006, the Hawaii State Legislature funded a pilot perinatal addiction clinic. The Perinatal Addiction Treatment Clinic of Hawaii was built on a harm-reduction model, encompassing perinatal care, transportation, child-care, social services, family planning, motivational incentives, and addiction medicine. We present the implementation model and results from our first one hundred three infants (103) seen over 3 years of operation of the program.</p> <p>Methods</p> <p>Referrals came from community health centers, hospitals, addiction treatment facilities, private physician offices, homeless outreach services and self-referral through word-of-mouth and bus ads. Data to describe sample characteristics and outcome was obtained prospectively and retrospectively from chart abstraction and delivery data. Drug use data was obtained from the women's self-report and random urine toxicology during the pregnancy, as well as urine toxicology at the time of birth on mothers, and urine and meconium toxicology on the infants. Post-partum depression was measured in mothers with the Edinburgh Post-Partum depression scale. Data from Path clinic patients were compared with a representative cohort of women delivering at Kapiolani Medical Center for Women and Children during the same time frame, who were enrolled in another study of pregnancy outcomes. Ethical approval for this study was obtained through the University of Hawaii Committee for Human Studies.</p> <p>Results</p> <p>Between April 2007 and August 2010, 213 women with a past or present history of addiction were seen, 132 were pregnant and 97 delivered during that time. 103 live-born infants were delivered. There were 3 first-trimester Spontaneous Abortions, two 28-week intrauterine fetal deaths, and two sets of twins and 4 repeat pregnancies. Over 50% of the women had lost custody of previous children due to substance use. The majority of women who delivered used methamphetamine (86%), either in the year before pregnancy or during pregnancy. Other drugs include marijuana (59.8%), cocaine (33%), opiates (9.6%), and alcohol (15.2%). Of the women served, 85% smoked cigarettes upon enrollment. Of the 97 women delivered during this period, all but 4 (96%) had negative urine toxicology at the time of delivery. Of the 103 infants, 13 (12.6%) were born preterm, equal to the state and national average, despite having many risk factors for prematurity, including poverty, poor diet, smoking and polysubstance use. Overwhelmingly, the women are parenting their children, > 90% retained custody at 8 weeks. Long-term follow-up showed that women who maintained custody chose long-acting contraceptive methods; while those who lost custody had a very high (> 50%) repeat pregnancy rate at 9 months post delivery.</p> <p>Conclusion</p> <p>Methamphetamine use during pregnancy doesn't exist is isolation. It is often combined with a multitude of other adverse circumstances, including poverty, interpersonal violence, psychiatric comorbidity, polysubstance use, nutritional deficiencies, inadequate health care and stressful life experiences. A comprehensive harm reduction model of perinatal care, which aims to ameliorate some of these difficulties for substance-using women without mandating abstinence, provides exceptional birth outcomes and can be implemented with limited resources.</p

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

Background: Osteoarthritis (OA) is an inflammatory disease of synovial joints involving the loss and degeneration of articular cartilage. The gold standard for evaluating cartilage loss in OA is the measurement of joint space width on standard radiographs. However, in most cases the diagnosis is made well after the onset of the disease, when the symptoms are well established. Identification of early biomarkers of OA can facilitate earlier diagnosis, improve disease monitoring and predict responses to therapeutic interventions. Methods: This study describes the bioinformatic analysis of data generated from high throughput proteomics for identification of potential biomarkers of OA. The mass spectrometry data was generated using a canine explant model of articular cartilage treated with the pro-inflammatory cytokine interleukin 1 β (IL-1β). The bioinformatics analysis involved the application of machine learning and network analysis to the proteomic mass spectrometry data. A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups. The proteins identified were considered to be potential biomarkers. Protein networks were also generated; from these networks, proteins pivotal to the classification were identified. Results: BioHEL correctly classified eighteen out of twenty-three samples, giving a classification accuracy of 78.3% for the dataset. The dataset included the four classes of control, IL-1β, carprofen, and IL-1β and carprofen together. This exceeded the other machine learners that were used for a comparison, on the same dataset, with the exception of another rule-based method, JRip, which performed equally well. The proteins that were most frequently used in rules generated by BioHEL were found to include a number of relevant proteins including matrix metalloproteinase 3, interleukin 8 and matrix gla protein. Conclusions: Using this protocol, combining an in vitro model of OA with bioinformatics analysis, a number of relevant extracellular matrix proteins were identified, thereby supporting the application of these bioinformatics tools for analysis of proteomic data from in vitro models of cartilage degradation