35 resultados para G82-621


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Purpose To provide a summary of the classic paper "Differences in the accommodation stimulus response curves of adult myopes and emmetropes" published in Ophthalmic and Physiological Optics in 1998 and to provide an update on the topic of accommodation errors in myopia. Summary The accommodation responses of 33 participants (10 emmetropes, 11 early onset myopes and 12 late onset myopes) aged 18-31 years were measured using the Canon Autoref R-1 free space autorefractor using three methods to vary the accommodation demand: decreasing distance (4 m to 0.25 cm), negative lenses (0 to -4 D at 4 m) and positive lenses (+4 to 0 D at 0.25 m). We observed that the greatest accommodation errors occurred for the negative lens method whereas minimal errors were observed using positive lenses. Adult progressing myopes had greater lags of accommodation than stable myopes at higher demands induced by negative lenses. Progressing myopes had shallower response gradients than the emmetropes and stable myopes; however the reduced gradient was much less than that observed in children using similar methods. Recent Findings This paper has been often cited as evidence that accommodation responses at near may be primarily reduced in adults with progressing myopia and not in stable myopes and/or that challenging accommodation stimuli (negative lenses with monocular viewing) are required to generate larger accommodation errors. As an analogy, animals reared with hyperopic errors develop axial elongation and myopia. Retinal defocus signals are presumably passed to the retinal pigment epithelium and choroid and then ultimately the sclera to modify eye length. A number of lens treatments that act to slow myopia progression may partially work through reducing accommodation errors.

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For the first time, we have fabricated and tested conductometric sensors based on oxidized liquid galinstan towards NO2 and NH3 gases at low operating temperatures. Galinstan based films on silicon substrates have been studied with two different loadings. Surface morphology of the films was investigated by means of field emission scanning electron microscopy (FESEM). The sensor with higher galinstan loading showed a better sensitivity, which can be attributed to a higher surface area, as confirmed by SEM. At 100°C, a detection limit as low as 1 and 20 ppm was measured for NO2 and NH3, respectively.

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Uterine leiomyomata (UL), the most prevalent pelvic tumors in women of reproductive age, pose a major public health problem given their high frequency, associated morbidities, and most common indication for hysterectomies. A genetic component to UL predisposition is supported by analyses of ethnic predisposition, twin studies, and familial aggregation. A genome-wide SNP linkage panel was genotyped and analyzed in 261 white UL-affected sister-pair families from the Finding Genes for Fibroids study. Two significant linkage regions were detected in 10p11 (LOD = 4.15) and 3p21 (LOD = 3.73), and five additional linkage regions were identified with LOD scores > 2.00 in 2q37, 5p13, 11p15, 12q14, and 17q25. Genome-wide association studies were performed in two independent cohorts of white women, and a meta-analysis was conducted. One SNP (rs4247357) was identified with a p value (p = 3.05 x 10(-8)) that reached genome-wide significance (odds ratio = 1.299). The candidate SNP is under a linkage peak and in a block of linkage disequilibrium in 17q25.3, which spans fatty acid synthase (FASN), coiled-coil-domain-containing 57 (CCDC57), and solute-carrier family 16, member 3 (SLC16A3). By tissue microarray immunohistochemistry, we found elevated (3-fold) FAS levels in UL-affected tissue compared to matched myometrial tissue. FAS transcripts and/or protein levels are upregulated in various neoplasms and implicated in tumor cell survival. FASN represents the initial UL risk allele identified in white women by a genome-wide, unbiased approach and opens a path to management and potential therapeutic intervention.

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The aim of this study was to identify and describe the types of errors in clinical reasoning that contribute to poor diagnostic performance at different levels of medical training and experience. Three cohorts of subjects, second- and fourth- (final) year medical students and a group of general practitioners, completed a set of clinical reasoning problems. The responses of those whose scores fell below the 25th centile were analysed to establish the stage of the clinical reasoning process - identification of relevant information, interpretation or hypothesis generation - at which most errors occurred and whether this was dependent on problem difficulty and level of medical experience. Results indicate that hypothesis errors decrease as expertise increases but that identification and interpretation errors increase. This may be due to inappropriate use of pattern recognition or to failure of the knowledge base. Furthermore, although hypothesis errors increased in line with problem difficulty, identification and interpretation errors decreased. A possible explanation is that as problem difficulty increases, subjects at all levels of expertise are less able to differentiate between relevant and irrelevant clinical features and so give equal consideration to all information contained within a case. It is concluded that the development of clinical reasoning in medical students throughout the course of their pre-clinical and clinical education may be enhanced by both an analysis of the clinical reasoning process and a specific focus on each of the stages at which errors commonly occur.

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The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.